Prevalence of Sleep Problems Among Chinese Medical Students: A Systematic Review and Meta-Analysis

Investigation on the association between college students' smartphone-related behaviors and sleep quality during COVID-19

OBJECTIVE

This study examines the quantifiable effects of pre-sleep smartphone use on sleep quality among college students during the COVID-19 pandemic, aiming to identify high-risk behaviors and inform targeted interventions.

METHODS

Based on data from 508 students of different genders and academic years, the study first conducted univariate and multivariate logistic regression analyses to explore the association between smartphone-related behaviors and sleep quality. Subsequently, the adjusted smartphone behaviors were stratified by gender(male/female) and academic year(freshmen/Sophomore/juniors) into subsets for further subgroup analysis, aiming to examine the relationship and impact of smartphone-related behaviors on sleep disturbancess across different genders and academic years.

RESULTS

he analysis revealed that specific pre-sleep activities were significantly associated with sleep quality. Notably, playing games before sleep (OR=6.071, p<0.001), late-night phone use (OR=2.824, p=0.002), having the phone off during sleep (OR=3.311, p<0.001), and using social media apps (OR=2.797, p=0.005) were linked to an increased risk of sleep disturbancess. Conversely, video-watching (OR=0.349, p=0.007) and moderate music listening (OR=0.220, p=0.004) were associated with a reduced risk of sleep disturbancess. Further analysis indicated that behaviors such as playing games and having the phone off during sleep significantly increased the risk of sleep disturbancess across different genders and academic years (OR>1, p<0.05).

CONCLUSION

During the COVID-19 pandemic, smartphone-related behaviors such as having the phone off during sleep, playing games before sleep, and using social media apps were identified as risk factors affecting sleep quality. This study provides empirical evidence for developing interventions aimed at improving sleep quality among college students in the context of heightened stress and disrupted routines caused by the pandemic.

Epidemiology of sleep disturbances among medical students in the Middle East and North Africa: a systematic review and meta-analysis

Background

Sleep disturbances and their associated health issues are common among medical students. Despite this, the epidemiology of sleep disturbances among medical students in the Middle East and North Africa (MENA) region remains inadequately understood. Our objective was to synthesise the prevalence of sleep disturbances, including poor sleep quality, insufficient sleep duration, and excessive daytime sleepiness (EDS), and their variation in relation to academic performance and stress levels.

Methods

We performed a systematic review and meta-analysis. Two independent reviewers searched PubMed, Web of Science, Google Scholar, and the reference lists of relevant studies and reviews up to May 2024. We assessed the quality of the included studies using a risk of bias tool. We performed meta-analyses using random-effects models and used Cochran's Q between-subgroups statistic to test for differences across subgroups. We used the I2 statistic to assess the statistical heterogeneity. Further, we assessed the publication bias using Doi plots.

Results

We included 150 studies conducted in 16 MENA countries. We found that 59.1% of medical students suffer from poor sleep quality (Pittsburgh Sleep Quality Index mean (x̄) = 8.5; 95% confidence interval (CI) = 7.0-10.1), 59.8% have insufficient sleep duration (<7 hours per night) averaging 6.1 hours per night (95% CI = 5.4-6.9), and 38.4% experience EDS (Epworth Sleepiness Scale x̄ = 8.6; 95% CI = 8.0-9.1). Our results indicate a significantly higher prevalence of poor sleep quality among students with moderate or high stress levels during the preclinical training period and in low-income MENA countries. A significantly higher prevalence of insufficient sleep duration was found among students during preclinical academic years. A significantly higher prevalence of EDS was found among students in public medical schools and those in low-income MENA countries. We observed no differences in poor sleep quality and EDS between students with poor and good academic performance.

Conclusions

Our findings highlight the substantial prevalence of sleep disturbances among MENA medical students. Medical schools must address this critical issue with targeted, locally informed, and culturally appropriate interventions. Further research is needed to assess the association between sleep disturbances and identify factors for tailored interventions that mitigate the adverse consequences on medical students' health and well-being.

Registration

Open Science Framework BF2A6.

Knowledge, Attitude and Practice of Medical Students Towards Insomnia and Traditional Chinese Medicine Treatment

BACKGROUND

To assess the Knowledge, Attitude, and Practice (KAP) of medical students at Hunan Medicine College towards insomnia and TCM treatment.

METHODS

The study included 676 medical students. More than half were female (64.20%), and 33.8% reported experiencing insomnia for over a week. Participants' KAP scores were evaluated on insomnia and TCM treatment using a scale.

RESULTS

The mean KAP scores for insomnia were 58.93%, 73.75%, and 64.94%, respectively, indicating insufficient knowledge but positive attitudes and moderate practices. TCM treatment scores were 78.18%, suggesting better awareness. Overall, 67.60% of medical students would choose TCM for insomnia treatment. Multivariable analysis revealed associations between choosing TCM and higher knowledge (OR = 1.30), positive attitude (OR = 1.46), better practice (OR = 3.44), and being in a later academic year (OR = 2.397).

CONCLUSION

The study underscores the need for targeted educational interventions to enhance understanding and promote effective practices among medical students, potentially improving their well-being and addressing insomnia more comprehensively.

Prevalence and influencing factors of sleep disturbance among medical students under the COVID-19 pandemic

BACKGROUND

Medical students may feel severe psychological stress during COVID-19, which might impair their ability to sleep. This research aimed to look at the risk factors for sleep disturbance and the prevalence of sleep disturbance among medical students.

METHODS

538 medical students in total were recruited for this research. Anxiety, depression, and sleep disturbance were assessed using the Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Pittsburgh Sleep Quality Index (PSQI). To evaluate the possible risk variables, we computed descriptive statistics for each assessment item and ran univariate and logistic regression analyses.

RESULTS

Medical students had a 63.6% prevalence of sleep disturbance (n = 342). According to logistic regression, introverted students are 1.77 times more likely than extroverted students to have sleep disturbance (OR = 1.77, 95% CI 1.08-2.91). Medical students with depression had a 5.6-times higher risk of sleep disturbance than those without depression (OR = 5.60, 95% CI 3.43-9.15). Additionally, medical students with anxiety were 3.95 times more likely than those without anxiety to have sleep disturbance (OR = 3.95, 95% CI 2.04-7.64).

CONCLUSIONS

According to this research, the COVID-19 pandemic caused significant sleep disturbance among medical students. Additionally, among medical students, introversion, anxiety, and depression were risk factors for sleep disturbance.

Impact of sleep quality on academic achievements of undergraduate medical students: a cross-sectional study from Saudi Arabia

BACKGROUND

Sleep is an active process that affects human health and quality of life. Sleep is essential for learning and memory consolidation. Good sleep is required for good academic performance. Sleep disorders are common among medical students, due to the high academic load, stressful life, and hectic schedule. Therefore, this study aims to assess sleep quality among medical students.

METHODS

A cross-sectional study was conducted among medical students at King Khalid University by using the Pittsburgh sleep quality index (PSQI) to assess sleep duration, sleep efficiency, sleep latency, and global PSQI score. Participants were enrolled from second to sixth year. Bivariate and multivariate logistic regression were used to predict factors related to poor sleep quality.

RESULTS

Out of 514 medical students, 453 (88.1%) of students exhibited poor sleep quality. Fourth year students were less likely to have poor sleep quality (AOR, 0.381; CI, 0.158-0.934) p = 0.035 and students with regular sleep schedule were more likely to be good sleepers (AOR,0.349; CI, 0.129-0.940) p = 0.037. Additionally, students who had more than five courses per semester more frequently had daytime sleepiness p = 0.03. However, Insufficient sleep was not significantly affected by factors like gender, different age groups, number of courses per semester, daytime sleeping, and students with varying Grade Point Averages (GPA).

CONCLUSION

Poor sleep quality is common among medical students, which may affect academic performance and general health. It is essential to educate them about good sleep hygiene and time management skills.

Sleep patterns and their associations with psychiatric symptoms among Chinese healthcare workers: a latent profile analysis

Background

Healthcare workers often encounter inadequate sleep conditions. However, limited research has examined the underlying sleep patterns among healthcare workers. This study aimed to identify sleep patterns in healthcare workers, explore predictors associated with various sleep patterns, and investigate the relationship between sleep patterns and psychiatric symptoms.

Methods

This cross-sectional study was conducted in Shenzhen, China, from April 2023 to June 2023. In total, data from 1,292 participants were included using a convenience sampling method. A latent profile analysis was conducted to identify sleep patterns based on the seven dimensions of the Pittsburgh Sleep Quality Index. Multinomial logistic regression analysis was conducted to investigate the influence of socio-demographic variables on each profile. A one-way ANOVA test was employed to examine the relationships between sleep patterns and psychiatric symptoms.

Results

Three distinct profiles were identified: good sleepers (63.9%), inefficient sleepers (30.3%), and poor sleepers (5.7%). Multinomial logistic regression analysis indicated that gender and marital status were predictors of various sleep patterns. The ANOVA revealed significant differences in psychiatric symptoms scores among the three sleep patterns; poor sleepers exhibited the highest levels of mental distress.

Conclusion

This study identified three distinct sleep patterns in healthcare workers and their significant associations with psychiatric symptoms. These findings contribute to the development of targeted intervention strategies aimed at improving sleep and reducing psychiatric symptoms among healthcare workers.

Sleep quality and related factors among healthcare workers in designated quarantine hospital site in post-pandemic based on the health ecological model: a cross-sectional study in Nanjing, China

AIMS

This study aims to assess the status and related factors among healthcare workers (HCWs) in designated quarantine-hospital-site (DQHS) based on the model of health ecology.

METHODS

The cross-sectional study was conducted from April to May, 2022, which included 351 valid samples. We measured sleep quality using the Pittsburgh Sleep Quality Index, which encompasses seven dimensions: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each dimension is scored individually, contributing to an overall sleep quality score. Factors associated with the sleep quality of HCWs in DQHS were divided into individual, behavioral, interpersonal and social dimensions. Hierarchical linear regressions were conducted to identify the potential factors associated with sleep quality among HCWs in DQHS.

RESULTS

HCWs in DQHS had a statistically higher sleep quality than the Chinese national norm. HCWs who were female, afraid of Coronavirus disease, had more negative emotions, frequently worked overtime, were married, and had a higher income were more likely to experience worse sleep quality (p < 0.05), while those who worked between 51 and 70 h weekly, treated over 10 patients daily, and engaged in more health behaviors may have better sleep quality (p < 0.05).

CONCLUSION

This study revealed a worrying level of sleep quality among HCWs in DQHS. The government, hospital managers, and families should collaborate to ensure the sleep quality of HCWs in DQHS.

Differences and common ground in the frameworks of health-related quality of life in traditional Chinese medicine and modern medicine: a systematic review

PURPOSE

This systematic review aims to explore the conceptualization of health-related quality of life (HRQoL) in China. With HRQoL influenced by both modern medicine (MM) and traditional Chinese medicine (TCM), the study seeks to identify differences and common ground between the frameworks of MM and TCM as defined in the literature.

METHOD

A systematic literature search was conducted across three Chinese databases and four English databases. The data was extracted including title, author(s), publication year, region, aim, method, category, and result. When sorting data, we broke down the HRQoL frameworks into concepts, domains and facets, with a focus on overlapped facets between the frameworks of MM and TCM.

RESULTS

A total of 31 studies were included. In the perspective of TCM, HRQoL is centered around three key 'concepts': (1) 'xingshentongyi' (unity of body and spirit), (2) 'tianrenheyi' (harmony between man and nature), and (3) 'qiqing' (seven emotional forms). In contrast, the MM framework comprises 'physical,' 'mental,' 'social,' and 'environment' domains. Out of the 59 unique facets identified, 28 are common to both TCM and MM, 9 specific to TCM, and 22 specific to MM. 'Appetite,' 'sleep,' and 'energy' are the most frequently mentioned facets in both frameworks.

CONCLUSION

The concept of HRQoL in China encompasses frameworks rooted in both TCM and MM. While TCM and MM have distinct healthcare approaches, they share overlapping domains when measuring HRQoL through questionnaires. Furthermore, TCM and MM demonstrate considerable convergence in terms of HRQoL facets, showing the potential for utilizing HRQoL instruments across different cultural settings.

Screen Time Among Medical and Nursing Students and Its Correlation With Sleep Quality and Attention Span: A Cross-Sectional Study

BACKGROUND

 Screen time is increasing among students and is also known to affect their lifestyle and health. The study investigated the correlation of screen time with sleep quality and attention span.

METHODS

A cross-sectional study was conducted among undergraduate medical and nursing students in November 2021. A total of 192 students were selected randomly and investigated using a structured questionnaire. Sleep behavior was assessed using the Pittsburg Sleep Quality Index. Screen time and attention span were measured for each participant. The screen time data was reported as the median with an IQR. Pearson's correlation was performed to assess the correlation between screen time and sleep behavior and screen time and attention span.

RESULTS

 The median screen time for 28 days was 260 (192.2-326.7) hours, and the median non-academic screen time was 250.0 (172.3-328.0) hours. Subjective sleep quality was good among 163 (84.9%) of the study participants. Global sleep quality was poor among 91 (42.2%) participants. The median score of the digit span forward was 6.00 (IQR: 5.00-7.00), and the median score of the digit span backward was 5.00 (IQR: 4.00-6.00). The global sleep score had a strong positive correlation with screen time, with a Pearson's correlation coefficient of 0.86. Forward and backward attention spans were not correlated with sleep scores, with correlation coefficients of 0.037 and 0.071, respectively.

CONCLUSION

 Screen time is increasing significantly among medical and nursing undergraduate students, and their sleep is also getting affected. Emphasis should be given to the balance between digitalization and health.

Facebook addiction and sleep problems in peruvian university students after the COVID-19 pandemic

Background

During the COVID-19 pandemic, studies have reported an increase in sleep problems and problematic use of social media platforms such as Facebook among university students. This study assessed Facebook addiction and sleep problems among Peruvian university students following the COVID-19 pandemic, as well as the factors associated with these issues.

Methods

A cross-sectional study was conducted with a sample of 352 participants from different regions of Peru. The Jenkins Sleep Scale (JSS-4) and the Bergen Facebook Addiction Scale (BFAS) were used to assess sleep problems and Facebook addiction, respectively. Prevalence ratios (PR) were calculated using a simple Poisson regression with robust variance.

Results

The study found that 16.2 % of the participants were addicted to Facebook and 12.5 % reported sleep problems. The results also showed that older age (PR: 0.99; 95 % CI: 0.98-0.99) and physical activity (PR: 0.81; 95 % CI: 0.70-0.94) were associated with a lower likelihood of having sleep problems, while being physically active (PR: 0.55; 95 % CI: 0.33 to 0.90) was associated with a lower probability of having Facebook addiction problems.

Conclusions

The Peruvian university students who participated in this study reported sleep problems in one-eighth of the sample, and one in six university students reported Facebook addiction problems. The frequency of presenting Facebook addiction and sleep problems was lower in those with older age and engaging in physical activity.

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

OBJECTIVE

The sleep of healthcare students is worth discovering. Mental health and self-rated health are thought to be associated with sleep quality. As such, valid instruments to assess sleep quality in healthcare students are crucial and irreplaceable. This study aimed to investigate the measurement properties of the Sleep Quality Questionnaire (SQQ) for Chinese healthcare students.

METHODS

Two longitudinal assessments were undertaken among healthcare students, with a total of 595, between December 2020 and January 2021. Measures include the Chinese version of the SQQ, Patient Health Questionnaire-4 (PHQ-4), Self-Rated Health Questionnaire (SRHQ), and sociodemographic questionnaire. Structural validity through confirmatory factor analysis (CFA) was conducted to examine factor structure of the SQQ. T-tests and ANOVAs were used to examine sociodemographic differences in sleep quality scores. Multi Group CFA and longitudinal CFA were respectively used to assess cross-sectional invariance and longitudinal invariance across two-time interval, i.e., cross-cultural validity. Construct validity, internal consistency, and test-retest reliability were correspondingly examined via Spearman correlation, Cronbach's alpha and McDonald's omega, and intraclass correlation coefficient. Multiple linear regression analysis was performed to examine incremental validity of the SQQ based on the PHQ-4 and SRHQ as indicators of the criterion variables.

RESULTS

CFA results suggested that the two-factor model of the SQQ-9 (item 2 excluded) had the best fit. The SQQ-9 scores differed significantly by age, grade, academic stage, hobby, stress coping strategy, anxiety, depression, and self-rated health subgroups. Measurement invariance was supported in terms of aforesaid subgroups and across two time intervals. In correlation and regression analyses, anxiety, depression, and self-rated health were moderately strong predictors of sleep quality. The SQQ-9 had good internal consistency and test-retest reliability.

CONCLUSION

Good measurement properties suggest that the SQQ is a promising and practical measurement instrument for assessing sleep quality of Chinese healthcare students.

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

BACKGROUND

The RU_SATED scale is a multidimensional instrument measuring sleep health, consisting of Regularity, Satisfaction, Alertness, Timing, Efficiency, Duration dimensions. We adapted and validated the Chinese RU_SATED (RU_SATED-C) scale.

METHODS

The RU_SATED-C scale was developed through a formal linguistic validation process and was validated in an observational longitudinal survey design. Healthcare students completed the RU_SATED scale, Sleep Quality Questionnaire, and Patient Health Questionnaire-4 among two sites of Hangzhou and Ningbo, China. Psychometric assessments included structural validity, longitudinal measurement invariance, convergent and divergent validity, internal consistency, and test-retest reliability.

RESULTS

A total of 911 healthcare students completed the RU_SATED-C scale at baseline (Time 1, T1) and follow-up (Time 2, T2) with an average time interval of 7 days + 5.37 h. Confirmatory factor analysis (CFA) confirmed a single-factor model and resulted in an acceptable model fit. The two-factor model previously found in the Japanese version fit better than the one-factor model, whereas the one-factor model fit had a better fit than the two-factor model found in the English version. Longitudinal CFA resulted in negligible changes in fit indices for four forms of increasingly restrictive models and supported that a single-factor model was equivalent over time. The data also endorsed longitudinal measurement invariance among the two-factor models found in the English and Japanese samples. The RU_SATED-C scale total score displayed a moderately strong negative correlation with sleep quality; however, negligible associations were observed with anxiety and depression. Ordinal Cronbach's alpha and Ordinal McDonald's omega at T1 and T2 ranged from suboptimal to acceptable. The RU_SATED-C scale and all items were significantly correlated across time intervals.

CONCLUSION

The RU_SATED-C scale is an easy-to-use instrument with potentially valid data for the measurement of multidimensional sleep health. Use of the RU_SATED-C scale can help raise awareness of sleep health and could pave the way for important efforts to promote healthy sleep.

Depression and Anxiety Mediate the Association between Sleep Quality and Self-Rated Health in Healthcare Students

OBJECTIVES

This study aimed to investigate factors associated with sleep quality in healthcare students and to determine whether depressive and anxiety symptoms may explain some of the associations between sleep quality and self-rated health.

STUDY DESIGN

This is a cross-sectional study at wave one.

METHODS

A total of 637 healthcare students were recruited via a stratified random sampling method in Hangzhou, China. The Sleep Quality Questionnaire (SQQ) and the four-item Patient Health Questionnaire (PHQ-4) were used to assess sleep quality and depressive and anxiety symptoms, respectively. Self-rated health was assessed via a self-developed questionnaire of both physical and psychological health. Structural equation modeling was used to examine the direct and indirect effects of sleep quality on self-rated health through depressive and anxiety symptoms.

RESULTS

Students engaged in part-time employment (p = 0.022), with poor perceived employment prospects (p = 0.009), and who did not participate in recreational sports (p = 0.008) had worse sleep quality. Structural equation modeling revealed a significant total effect of sleep quality on self-rated health (b = 0.592, p < 0.001), a significant direct effect of both sleep quality and depressive and anxiety symptoms on self-rated health (b = 0.277, 95% CI: 0.032-0.522), and a significant indirect effect of sleep quality on self-rated health through depressive and anxiety symptoms (b = 0.315, 95% CI: 0.174-0.457).

CONCLUSIONS

Depressive and anxiety symptoms partially explain the association between sleep quality and self-rated health. Intervening upon sleep quality, depressive, and anxiety symptoms may bolster the self-rated health of healthcare students.

Sleep - the guarantee of health! Does the environmental perception characteristics of urban residential areas affect residents' sleep quality?

A complex urban living environment and residents' sleep quality are intrinsically linked. Nonetheless, there is little evidence that the residential environment affects sleep quality. Based on the results of subjective questionnaires, this study uses the multiple regression combined with mediation analysis to construct a mechanical model of the impact of urban residential environmental perception characteristics on residents' sleep quality. Moreover, the differences among the influence intensities of the significant factors are compared and the results show that (1) in low-density environments (FAR < 2) and lower floors (4-6), residents sleep longer and have better sleep quality; (2) the environmental quality and service facilities of the physical environment and the sense of safety in the social environment have a significant impact on residents' sleep quality; and (3) the mental health of residents play a significant intermediary role in the relationship between social environment and sleep quality, with the highest effect accounting for 33.88%. The influence mechanisms of various environmental factors in a residential area on sleep quality were revealed and a more refined design basis for a healthy urban living environment, community renewal, and renovation was provided.

Effectiveness of Multidomain Dormitory Environment and Roommate Intervention for Improving Sleep Quality of Medical College Students: A Cluster Randomised Controlled Trial in China

Medical students are vulnerable to sleep disorders, which could be further exaggerated by poor dormitory environment and roommate behaviour. However, there is little evidence of whether dormitory environment intervention is effective in improving the sleep quality of medical college students in developing countries. The present study aimed to evaluate the effects of a comprehensive multidomain intervention on dormitory environment and roommate behaviour among medical college students in China. In this cluster randomised controlled trial, a total of 106 dormitories (364 students) were randomly allocated into an intervention group (55 dormitories, 193 students) and a control group (51 dormitories, 171 students). The intervention group received a three-month intervention with multiple components to improve or adapt to sleep environments in dormitories; the control group received no intervention. Primary and secondary outcomes were measured at study enrolment and three months later for both groups. The linear mixed-effects models showed that, compared with the control group, the intervention was associated with a significantly decreased Pittsburgh Sleep Quality Index (β = -0.67, p = 0.012), and a marginally significant effect on reducing roommates' influence on sleep schedule (β = -0.21, p = 0.066). Students in the intervention group rated "making dormitory sleep rules" and "wearing eye masks" as the most effective intervention measures. These findings could contribute to the limited body of scientific evidence about sleep intervention in Chinese medical students and highlight the importance of dormitory sleep environments in maintaining sleep quality.

Deteriorated sleep quality and influencing factors among undergraduates in northern Guizhou, China

Background

The sleep quality of undergraduates is considerably worse than that in general population, a cross sectional study was conducted to evaluate sleep quality and identify related factors.

Methods

All participants from the freshmen to senior were recruited by the stratified cluster sampling from December 1, 2018 to January 12, 2019. The questionnaire used in this research was primarily composed of three sections: demographic characteristics, Pittsburgh Sleep Quality Index (PSQI) questionnaire and influencing factors of sleep quality. The data were analyzed using SPSS 18.0.

Results

A total of 1,063 valid questionnaires were collected. Among them, 53.7% subjects suffered poor sleep quality. PSQI general score was 5.94 ± 2.73. There were significantly differences in sleep quality in sex, majors and grades. The survey reported that women suffered worse sleep quality than that of men, and medical students suffered worse sleep quality than non-medical students. Meanwhile, it also found that freshmen had better sleep quality than that of sophomores and juniors, sophomores suffered worst sleep quality. The logistic regression analysis showed that bad physical condition (OR (Odds ratio): 2.971 (2.034∼4.339)) and smoking (OR: 1.754 (1.258∼2.446)) were associated with poor sleep quality in males. However, more factors associated with poor sleep quality among females were found, including noisy dormitory environment (OR: 2.025 (1.354-3.030)), skipping breakfast more times per week (OR: 1.332 (1.031∼1.721)), drinking coffee before sleep (OR: 2.111 (1.155∼3.861)), playing with mobile phones for more than 45 minutes before sleep (OR: 1.745 (1.210∼2.515)), more time spent playing games per day (OR: 1.347 (1.048∼1.730)), bad physical condition (OR: 2.507 (1.797-3.497)), and severe academic stress (OR: 1.561 (1.126-2.166)).

Conclusion

About half of college students experienced poor sleep, and poor sleep quality was prevalent in women, medical students, and sophomores. Moreover, there were more risk factors associated with the poor sleep quality of women than with men. Health policymakers should fully consider these factors in improving the sleep quality of college students.