Sleep Quality in Korean High School Students Is Associated With Lower Social Jetlag, Longer Weekday Time in Bed, and Less Self-Suppressive Defense Style
Article information
Abstract
Objective
Good sleep in adolescents may influence brain development and psychological problems such as anxiety and depression. Although social jetlag has been associated with sleep quality in adolescents, the association between other behavioral and personality factors and sleep quality in adolescents has not been elucidated.
Methods
Sleep-related behaviors, such as time in bed (TIB) on weekdays and weekends, social jetlag, and daytime sunlight exposure, were evaluated using various measurement tools such as sleep-related questionnaires, including defense style and morningness–eveningness questionnaires, insomnia severity index, Epworth Sleepiness Scale, and hospital anxiety and depression scale. This study involved 1,610 high school students.
Results
Multiple linear regression analysis revealed an association of better sleep quality with lesser social jetlag (β=0.085, t=3.217, p=0.001) and longer weekday TIB (β=-0.072, t=-2.634, p=0.009) after adjusting for age, sex, anxiety, depression, daytime sleepiness, weekday total sleep time, weekend oversleep, and mean daily sunlight exposure time. Furthermore, better sleep quality in adolescents was associated with lesser self-suppressive defense style (β=0.097, t=4.094, p<0.001) after adjusting for age, sex, anxiety, depression, chronotype, and daytime sleepiness.
Conclusion
Good sleep quality in adolescents may be related to behavioral factors, such as lower social jetlag and longer weekday TIB, and psychological factors, such as a less self-suppressive defense style.
INTRODUCTION
Good sleep quality is crucial in adolescents, as sleep can influence their physical and psychological development. Good sleep can prevent mental health problems in adolescents by promoting resilience [1-3]. Sleep behavior is associated with brain development. A previous study reported a correlation between weekday sleep duration and hippocampus gray matter volume in 290 healthy children and adolescents aged 5–18 years [4]. Adolescence depresCIMsive symptoms are partially mediated by sleep-related developmental changes, including short sleep duration and sleep quality [5]. Furthermore, in adolescents, anxiety is associated with sleep quality [6], and better sleep quality is associated with higher bidirectional resilience [2].
Adolescents with insomnia may exhibit maladaptive cognitions, such as cognitive inflexibility, interpretational biases, negative attribution styles, worry, and dysfunctional beliefs and attitudes about sleep [7]. A previous study reported a weak association between poor sleep quality and poor executive functions in adolescent girls [8], and an association of short sleep duration and poor sleep quality with poor executive functioning in adolescent boys [8]. However, the relationship between adolescent sleep and personality style has not been studied well.
In this study, we hypothesized that sleep quality in adolescents might be associated with certain sleep-related behaviors, such as weekend oversleep and social jetlag, as well as specific defense styles. We also investigated sleep quality-related sleep behaviors associated with certain defense styles. We hypothesized that certain sleep-related behaviors would be associated with the sleep quality of adolescents, and certain defense styles might be associated with sleep quality-related sleep behaviors.
METHODS
Participants
This study was a part of a local adolescent mental health survey conducted by the Haman-gun Community Mental Health Center, Gyeongsang Province, Republic of Korea. Other parts of the survey have been published elsewhere [9,10]. The survey was conducted in five high schools in Haman-gun between August and November, 2015. The purpose and procedure of the survey were explained to the teachers and students, and students who agreed to complete the survey were recruited. Participants were invited to complete self-reporting questionnaires about sleep-related behaviors, sleep quality, chronotype, daytime sleepiness, depression, and anxiety. The study protocol was approved by the Institutional Review Board of the Gyeongsang National University Hospital (IRB file number: 2015-06-004-004). Prior consent was obtained from the participants.
Measurement tools
Sleep-related questionnaire
Sleep patterns and habits of the participants were assessed based on the sleep-related questionnaires, including the items related to time in bed (TIB) and total sleep time (TST). Social jetlag was evaluated by calculating the absolute value of the difference in wake-up time between weekdays and weekends. Weekend oversleep was assessed by subtracting weekday TST from the weekend TST. Additionally, data about the daytime sunlight exposure, defined as the duration of any outdoor activity performed between 10:00 and 15:00 on weekdays and weekends, was collected. The mean daily sunlight exposure was assessed by computing the mean duration on weekdays and weekends.
Insomnia Severity Index
The Insomnia Severity Index (ISI), a self-reporting questionnaire encompassing seven items scored on a 5-point Likert scale (0–4), was used to assess insomnia severity [11]. A higher score indicates poor sleep quality. The Korean version of the ISI, which has adequate reliability and validity, was used in this study [12]. The Cronbach’s alpha was 0.809.
Defense Style Questionnaire
The Korean version of the Defense Style Questionnaire (DSQ), a psychometric instrument comprising 65 items, was used to examine individual thoughts and behaviors [13]. DSQ has been developed for assessing self-appraised conscious derivatives of defense styles and mechanisms [13]. Notably, it measures 16 defense mechanisms and is grouped into four defense styles: adaptive (sublimation, humor, denial, and omnipotence), self-inhibiting (suppression, undoing, reaction formation, and withdrawal), conflict-avoiding (isolation and resignation), and immature (passive aggression, consumption, fantasy, splitting, acting out, and projection).
Epworth Sleepiness Scale
The Epworth Sleepiness Scale (ESS) was used to measure the daytime sleepiness behavior of the participants. Participants rated their chances of dozing off or falling asleep while being involved in eight situations. The ESS comprises eight items scored on a 4-point Likert scale (0–3). A higher total score indicates severe daytime sleepiness. The Korean version of the ESS, which has adequate reliability and validity, was used in this study [14]. The Cronbach’s alpha was 0.655.
Hospital Anxiety and Depression Scale
The Hospital Anxiety and Depression Scale (HADS) comprises two subscales—HADS-Anxiety (HADS-A) and HADS-Depression (HADS-D)—encompassing 14 items scored on a 4-point Likert scale (0–3). A higher score indicates higher anxiety and depression levels [15]. A total subscale score of ≥8 points represents substantial anxiety or depression. The Korean version of the HADS, which has adequate validity and reliability, was used in this study [16]. The Cronbach’s alpha of the HADS-A and HADS-D were 0.834 and 0.705, respectively.
Morningness–Eveningness Questionnaire
The Morningness–Eveningness Questionnaire (MEQ) was used to determine the chronotype of the participants. It comprises 19 items, and the total score ranges from 16 to 86. A higher score indicates a higher level of morningness. The Korean version of the MEQ, which has adequate validity and reliability, was used in this study [17,18]. The Cronbach’s alpha was 0.696.
Data analysis
Independent t-tests were employed to determine the differences between male and female participants. Multiple linear regression analyses were conducted to determine the predictors of sleep quality. First, the behavioral predictors of sleep quality were identified using ISI scores as dependent variables and social jetlag, weekend oversleep, weekday TIB, weekday TST, age, sex, anxiety, depression, and daytime sleepiness as possible predictors of sleep quality. Another multiple linear regression analysis was performed to determine the predictors of sleep quality among the four defense styles using the ISI score as the dependent variable and defense style, age, sex, anxiety, depression, chronotype, and daytime sleepiness as possible predictors and confounders. Subsequently, whether sleep-related behavioral predictors of sleep quality are associated with defense styles was also evaluated. Notably, multiple linear regression analyses were conducted to determine which defense style predicted sleep-related variables to better predict the sleep quality.
RESULTS
A total of 1,610 adolescents participated in this study, of which 871 (54.1%) were females. The mean age of the participants was 16.9 years (standard deviation=0.886). Notably, 542 (33.7%), 532 (33.0%), and 536 (33.3%) were first-, second-, and third-grade students, respectively. Sleep-related behaviors, including weekday TIB, weekend TIB, weekday TST, weekend TST, weekday sunlight exposure time from 10:00 to 15:00, weekend sunlight exposure time from 10:00 to 15:00, and mean daily sunlight exposure time from 10:00 to 15:00, are presented in Table 1. Mean TST during weekdays was longer in males (6.24±1.54 h) than females (5.83± 1.24 h) (t[1,608]=5.86, p<0.001) (Table 1). Sunlight exposure time from 10:00 to 15:00 during weekdays was also longer in males (0.71±0.83 h) than females (0.49±0.69 h) (t[1,608]=5.95, p<0.001) (Table 1). Furthermore, 84 students had ISI scores (i.e., the ISI cutoff value) of >15, 713 students had an ESS score greater than 9, and 368 students had an ESS score greater than 11, indicating severe daytime sleepiness. Additionally, 471 and 494 students had HADS-A score of >8 and HADS-D score of >8, respectively.
Demographic and clinical characteristics of the participants
Multiple linear regression analysis revealed an association of better sleep quality (that is, lower ISI score) in adolescents with lesser social jetlag (β=0.085, t=3.217, p=0.001) and longer weekday TIB (β=-0.072, t=-2.634, p=0.009) after adjusting for age, sex, anxiety, depression, daytime sleepiness, weekday TST, weekend oversleep, and mean daily sunlight exposure time (Table 2). Another multiple linear regression analysis revealed an association between better sleep quality (lower ISI scores) in adolescents and lesser self-suppressive defense style (β=0.097, t=4.094, p<0.001) after adjusting for age, sex, anxiety, depression, chronotype, and daytime sleepiness (Table 3).
Multiple linear regression model predicting sleep quality
Multiple linear regression model predicting sleep quality regarding defense style
Higher social jetlag in adolescents was significantly associated with lesser use of adaptive defense style (β=-0.073, t=-2.807, p=0.005) after adjusting for age, sex, anxiety, depression, sleep quality, daytime sleepiness, and use of immature defense style (Table 4). Furthermore, longer weekday TIB in adolescents was significantly associated with lesser use of adaptive defense style (β=-0.084, t=-3.262, p=0.001) after adjusting for age, sex, anxiety, depression, sleep quality, daytime sleepiness, and use of immature defense style (Table 5).
Multiple linear regression model predicting social jetlag
Multiple linear regression model predicting weekday time in bed
DISCUSSION
Our findings revealed that the lower the social jetlag and longer the weekday TIB, the better the sleep quality in adolescents. Additionally, better sleep quality was associated with lesser use of self-suppressive defense style, whereas lower social jetlag and shorter weekday TIB were associated with greater use of adaptive defense style among adolescents.
This study indicates that social jetlag and weekday TIB can predict sleep quality in adolescents. A previous study reported an association between higher (≥2 h) social jetlag and poor sleep quality based on the ISI score in Chinese adolescents [19]. Similarly, another study involving Japanese high school students also reported an association between social jetlag of >2 h and poor sleep quality [20]. In the present study, social jetlag was considered a continuous variable, and it was significantly associated with sleep quality. Social jetlag and weekday TIB were significant predictors of sleep quality, in addition to weekday TST and weekend oversleep. Previous studies did not specifically use sleep variables such as in our study, resulting in the lack of reports regarding the association between TIB and insomnia in adolescents. Our results imply that waking up regularly at consistent timing and longer TIB on weekdays may improve sleep quality in adolescents.
Our findings also revealed that lesser use of a self-suppressive defense style predicts better sleep quality. A previous study revealed and association between immature defense style and poor sleep quality in patients with colorectal cancer [21]. In the present study, self-suppressive defense style other than the immature style significantly predicted the sleep quality. A self-suppressive defense style represents a tendency to hide inner psychological conflicts and impulses rather than expressing them honestly [13]. Our results imply that expressing their inner feelings, negative emotions, and bitterness openly to others may improve sleep quality in adolescents.
Our findings also revealed that lesser use of a self-suppressive defense style predicts better sleep quality. A previous study revealed and association between immature defense style and poor sleep quality in patients with colorectal cancer [21]. In the present study, self-suppressive defense style other than the immature style significantly predicted the sleep quality. A self-suppressive defense style represents a tendency to hide inner psychological conflicts and impulses rather than expressing them honestly [13]. Our results imply that expressing their inner feelings, negative emotions, and bitterness openly to others may improve sleep quality in adolescents.
We investigated sleep quality-related variables (social jetlag and weekday TIB) and found their association with adaptive defense styles. Notably, lower social jetlag and longer weekday TIB were associated with greater and lesser use of adaptive defense styles, respectively. To the best of our knowledge, this has not been previously reported. The cognitive behavioral approaches intended to reduce social jetlag and increase weekday TIB might have different effects on adaptive defense styles.
This study aimed to identify decisive sleep-related variables associated with sleep quality in adolescents. Cognitive behavioral interventions can improve adolescent sleep quality [7]. Consistently, our results indicated that the behavioral approach focusing on social jetlag and weekday TIB may improve sleep quality in adolescents. However, caution is needed while increasing weekday TIB when a decreased use of adaptive defense style is involved.
This study has a few limitations. First, we could not determine the causal relationship between the variables because of the crosssectional design of the study. Second, all variables were acquired using self-reporting questionnaires. Objective evaluations using actigraphy or polysomnography are required in future studies. Nevertheless, despite these limitations, this study used several meaningful confounders, such as excessive daytime sleepiness, depression, and anxiety, for multiple linear regression analyses.
This study revealed that better sleep quality in adolescents was associated with behavioral factors, such as lower social jetlag and longer weekday TIB, and psychological factors, such as a self-suppressive defense style. However, each behavioral factor was associated with an adaptive defense style in the opposite direction. Consequently, weekday TIB in adolescents to improve sleep quality should be increased cautiously, as it may further decrease the use of adaptive defense style.
Notes
The authors have no potential conflicts of interest to disclose.
Availability of Data and Material
The datasets generated or analyzed during the study are available from the corresponding author on reasonable request.
Author Contributions
Conceptualization: Bong-Jo Kim, So-Jin Lee, Boseok Cha, Wooyoung Im. Data curation: So-Jin Lee, Dongyun Lee. Funding acquisition: Bong-Jo Kim, So-Jin Lee, Boseok Cha. Investigation: all authors. Methodology: So-Jin Lee, Dongyun Lee, Wooyoung Im, Jae-Won Choi. Project administration: all authors. Resources: Bong-Jo Kim, So-Jin Lee, Boseok Cha. Software: Bong-Jo Kim, So-Jin Lee, Boseok Cha. Supervision: Bong-Jo Kim, Boseok Cha. Validation: all authors. Visualization: Jae-Won Choi, Nuree Kang. Writing—original draft: Bong-Jo Kim, So-Jin Lee, Boseok Cha, Jae-Won Choi. Writing—review & editing: all authors.
Funding Statement
This study was supported by a grant from the Korean Mental Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (HM15C1108). This study was supported by a grant from Gyeongsang National University Hospital (2024).
Acknowledgements
None