Objectives: Nightmare disorder is highly prevalent in clinical settings and is highly comorbid with posttraumatic stress disorder (PTSD). In the current study, we aimed to develop and validate a semi-structured interview based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders-fifth edition for diagnosing nightmare disorder. Methods: We developed a Semi-Structured Clinical Interview for Nightmare Disorder (SCIN) in five steps: we interviewed 100 females (mean age, 24.6±5.88 years) using the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5); Structured Clinical Interview for DSM-IV Axis 1 Disorders, Research Version (SCID-I); and self-report questionnaires for nightmares (Disturbing Dream and Nightmare Severity Index, DDNSI), depression, state anxiety, trait anxiety, suicidal ideation, and insomnia. Two independent raters assessed the responses of the interviewees. The interrater reliability for the SCIN was calculated. Pearson’s correlation coefficient was used to assess convergent validity between SCIN and the DDNSI. Chi-square analyses were conducted to compare prevalence of PTSD based on nightmare disorder diagnosis. Results: Among the participants, 42% were diagnosed with nightmare disorder, 15% had subthreshold nightmare disorder, and 43% did not have nightmare disorder. Interrater reliability was moderate (Kappa=0.707, p<0.001). The semi-structured clinical interview showed good convergent validity with the DDNSI (r=0.639, p<0.001). Additionally, individuals who were identified as having nightmare disorder had higher levels of depression, state anxiety, trait anxiety, suicidal ideation, and insomnia (p<0.001). Based on the PTSD diagnosis using CAPS-5, the nightmare group had a higher proportion of PTSD diagnoses than the no-nightmare group (26.2% vs. 8.6%, respectively; χ2=38.41, p<0.001). Conclusions The semi-structured clinical interview for nightmare disorder appears to have good reliability and validity and can be used in clinical settings.

Objectives: Nightmare disorder is highly prevalent in clinical settings and is highly comorbid with posttraumatic stress disorder (PTSD). In the current study, we aimed to develop and validate a semi-structured interview based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders-fifth edition for diagnosing nightmare disorder. Methods: We developed a Semi-Structured Clinical Interview for Nightmare Disorder (SCIN) in five steps: we interviewed 100 females (mean age, 24.6±5.88 years) using the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5); Structured Clinical Interview for DSM-IV Axis 1 Disorders, Research Version (SCID-I); and self-report questionnaires for nightmares (Disturbing Dream and Nightmare Severity Index, DDNSI), depression, state anxiety, trait anxiety, suicidal ideation, and insomnia. Two independent raters assessed the responses of the interviewees. The interrater reliability for the SCIN was calculated. Pearson’s correlation coefficient was used to assess convergent validity between SCIN and the DDNSI. Chi-square analyses were conducted to compare prevalence of PTSD based on nightmare disorder diagnosis. Results: Among the participants, 42% were diagnosed with nightmare disorder, 15% had subthreshold nightmare disorder, and 43% did not have nightmare disorder. Interrater reliability was moderate (Kappa=0.707, p<0.001). The semi-structured clinical interview showed good convergent validity with the DDNSI (r=0.639, p<0.001). Additionally, individuals who were identified as having nightmare disorder had higher levels of depression, state anxiety, trait anxiety, suicidal ideation, and insomnia (p<0.001). Based on the PTSD diagnosis using CAPS-5, the nightmare group had a higher proportion of PTSD diagnoses than the no-nightmare group (26.2% vs. 8.6%, respectively; χ2=38.41, p<0.001). Conclusions The semi-structured clinical interview for nightmare disorder appears to have good reliability and validity and can be used in clinical settings.

OBJECTIVES: The current study aimed to explore the relationship between subjective sleep, emotions, social support and excessive daytime sleepiness (EDS), and extract the strongest predictor of EDS in female undergraduate students. METHODS: Our subjects consisted of 168 female undergraduate students (mean age 21.64±1.66). All participants completed Epworth Sleepiness Scale (ESS), Insomnia Severity Index, Hospital Anxiety and Depression Scale, Social Support Scale, and the Munich Chronotype Questionnaire. RESULTS: There were significant associations between insomnia, anxiety, depression with EDS, but not with subjective total sleep time of workdays and freedays. Also, 23.8% (n=40) of subjects endorsed clinical levels of EDS (ESS>10). Insomnia, anxiety, and depression were higher, and social support was lower in the EDS group compared to the normal group. Finally, we explored factors that influenced EDS, resulting in anxiety and social support being the strongest predictors of EDS. Social support was the strongest predictor of EDS compared to other predictors (β=-0.276, p<0.001). CONCLUSIONS: Results suggest that social support may be important to consider in female undergraduate students who experience EDS.
Anxiety ; Depression ; Female* ; Humans ; Sleep Initiation and Maintenance Disorders

OBJECTIVES: The current study aimed to explore the difference of dream themes, emotional intensity, and sleep parameters between nightmares and bad dreams in nightmare sufferers. METHODS: Twenty-four nightmare sufferers who endorsed clinical levels of nightmares (Disturbing Dream and Nightmare Severity Index Scores ≥10) recorded daily information about their dream themes using a modified version of the Typical Dreams Questionnaire, emotional intensity about their nightmares and bad dreams, and sleep for two weeks on a mobile device. RESULTS: Evil presence (35%) was reported with higher frequency in nightmares, whereas interpersonal conflicts (31%) were predominantly reported in bad dreams. Nightmares were rated substantially more emotionally intense than bad dreams. Especially, fear (Z=-2.118, p=0.034) was rated as being significantly higher in nightmares than bad dreams. There were differences on time in bed, wake after sleep onset, sleep efficiency on the days with nightmares or bad dreams compared to other days; however, there were no differences in sleep parameters between nightmares and bad dreams. CONCLUSIONS: The results suggest that nightmares may be qualitatively and quantitatively different from bad dreams in nightmare sufferers.
Dreams*

OBJECTIVES: The current study aimed to investigate individuals with night eating syndrome tendency in 115 female undergraduate sample based on night eating syndrome criteria, and analyze its association between mood, sleep, and alcohol use. METHODS: Subjects were divided into high and low tendency group of night eating syndrome based on the night eating questionnaire. All participants completed the Hospital Anxiety and Depression Scale, Insomnia Severity Index, Munich Chronotype Questionnaire, and Alcohol-Use Disorders Identification Test. Data was collected at two time points which were 3 months apart. All analyses were conducted using repeated measure ANOVA. RESULTS: Results indicated a significant difference between night eating syndrome tendency groups for anxiety and depression [F(1,113)=12.35, p=0.001 and F(1,113)=9.59, p=0.002, respectively]. Depression also had a significant time effect [F(1,113)=11.15, p=0.001]. Additionally, the high night eating syndrome tendency group had higher levels of insomnia severity [F(1,113)=24.34, p<0.001], eveningness [F(1,113)=15.09, p<0.001], and alcohol use [F(1,113)=6.73, p=0.011], and lower sleep efficiency [F(1,113)=6.30, p=0.014] compared to the low night eating syndrome tendency group. CONCLUSIONS: The high night eating syndrome tendency group had higher negative mood, sleep disturbance, and alcohol use compared to the low night eating syndrome tendency group. In summary, intervention for night eating syndrome may be important to consider in undergraduate students.
Alcohol Drinking ; Anxiety ; Circadian Rhythm ; Depression ; Eating* ; Feeding and Eating Disorders ; Female* ; Humans ; Sleep Initiation and Maintenance Disorders

OBJECTIVES: A majority of South Korean adolescents experience chronic sleep-deprivation due to social jet lag. In this study, we investigated gender differences in the relationship between social jet lag, depression, and obesity in Korean children and adolescents. METHODS: Our sample consisted of 4,380 adolescents (elementary school cohort n=2,141, middle school cohort n=2,239) who participated in the Korean Children and Youth Panel Survey. In order to analyze the gender differences in the relationship between sleep time difference, obesity and depression, t-test and chi-square test were utilized. RESULTS: Both cohorts revealed that the difference in weekday/weekend sleep duration (2.19+/-1.42 vs. 1.68+/-1.36, p<0.001) and depression levels (20.77+/-6.29 vs. 18.87+/-6.06, p<0.001) was significantly higher in girls than boys. However, body mass index was higher in boys than girls (20.86+/-3.42 vs. 20.04+/-2.51, p<0.001). Chi-square test revealed there was a significant difference between gender and weekday/weekend sleep discrepancy group (cutoff >2 hours). Both elementary school [chi2 (1)=8.73, p<0.05] and middle school cohorts [chi2 (1)=61.29, p<0.001] showed significant gender differences. CONCLUSIONS: There were especially more girls who reported a discrepancy of 2 or more hours of weekday/weekend sleep duration. In summary, intervention for social jet lag may be important to consider in adolescents.
Adolescent* ; Body Mass Index ; Child* ; Cohort Studies ; Depression* ; Female ; Humans ; Obesity*

Objectives: Currently, more than 80% of Korean police officers are assigned to a 24-hour rotating shift system. Shift workers’ sleep patterns change frequently, which may result in circadian rhythm desynchrony and sleep disturbance. The goal of this study was to compare sleep and cognitive functioning in different shift types. In addition, we analyzed the difference in cognitive functioning depending on whether shift workers took a night nap prior to their night shift. Methods: A total of 278 police officers working in Seoul (mean age 45.27±9.00 years, 88.5% male) participated, providing demographic information and completing selfreport questionnaires [Insomnia Severity Index, Epworth Sleepiness Scale, Munich ChronoType Questionnaire (Shift-work type), Patient Health Questionnaire-9]. Participants also performed the Psychomotor Vigilance Task, Trail Making Test A & B, and Stroop Test. Results: Participants included 57 (20.5%) day workers and 221 (79.5%) shift workers. The average Insomnia Severity Index score of shift workers was significantly higher than day workers (t=-2.861, p=0.005). Shift workers also slept about 0.78 hours less than day workers (t=4.730, p<0.001). Among shift workers, 66.3% (n=128) reported they took night naps prior to their night shift, sleeping on average 1.78 hours. Shift workers who took night naps had faster reaction times on the Trail Making Test A task [F(1, 136)=5.741, p=0.018], and significantly fewer Stroop C errors [F(1, 137)=5.638, p=0.019] than those who did not. Conclusions Shift working police officers reported significantly worse insomnia symptoms and slept less compared to their non-shift-working counterparts. Taking a night nap improved focused and selective attention.

Insomnia has been identified as a risk factor for suicide. Apart from its indirect influence on suicide risk through comorbid psychiatric illnesses, there is also strong empirical evidence that insomnia is an independent risk factor for suicide. Insomnia may affect suicide through different mechanisms, such as mood dysregulation, hopelessness, impulsivity, and sleep deprivation. Cognitive-behavioral therapy for insomnia (CBTI) is an evidence-based, non-pharmacological treatment that is effective in treating both primary and comorbid insomnia disorder. Treatment effects of CBTI can be extended to alleviate suicidality by improving sleep disturbance. Through a literature review, we summarize available data which suggests that CBTI may decrease suicidality risk, and provide clinical implications about utilizing CBTI for high risk suicidal patients.
Humans ; Impulsive Behavior ; Risk Factors ; Sleep Deprivation ; Sleep Initiation and Maintenance Disorders ; Suicide

OBJECTIVES: Bedtime procrastination is defined as going to bed later than intended, without having external reasons for doing so. Despite various studies investigating the new concept of bedtime procrastination, there have been no studies that have validated the Bedtime Procrastination Scale (BPS). Thus, this study aims to validate the BPS in Korean. METHODS: Two hundred twenty seven participants (mean age 22±2.39 years, 81.1% female) participated in the study. All participants completed the BPS, Insomnia Severity Index, Center for Epidemiologic Studies Depression Scale, Perceived Stress Scale, Depressive Symptom Inventory-Suicidality Subscale, and General Procrastination Scale (GPS). Exploratory factor analysis was used to determine number of factors. RESULTS: Exploratory factor analysis revealed support for one factor, which was consistent with the original study. Goodness of fit was adequate for the one factor model [χ²=59.369(df=27, p<0.001), Comparative Fit Index=0.963, Tucker-Lewis Index=0.951, Root Mean Square Error of Approximation= 0.073, Standardized Root Mean Square Residual=0.042]. Internal consistency was also adequate (Cronbach's alpha=0.86). Convergent validity was also high with the GPS (p<0.001, r=0.411). Correlations were also high with other questionnaires (p<0.05). CONCLUSIONS: The BPS is a reliable and valid measure for bedtime procrastination, and may have important clinical implications for sleep disorders.
Depression ; Epidemiologic Studies ; Factor Analysis, Statistical ; Humans ; Sleep Deprivation ; Sleep Initiation and Maintenance Disorders ; Sleep Wake Disorders ; Young Adult

Objectives: Bedtime procrastination is defined as going to bed later than intended, without having external reasons for doing so. According to previous studies, bedtime procrastination is strongly associated to usage of smart devices before bedtime. However, there is a lack of in-depth research about the function of smartphone usage before bedtime, and which applications are used frequently in association with bedtime procrastination. Therefore, the current study, preliminary research, investigates the usage patterns of smartphone applications of individuals with high levels of bedtime procrastination. Methods: Participants consisted of 20 adults (female=80%, age=20.9±2.05 years) who scored higher than 33 on the Bedtime Procrastination Scale. All participants completed a 7-day sleep diary, Insomnia Severity Index, and the Center for Epidemiological Studies Depression Scale. On the sleep diary, participants were asked to track the specific type of smartphone application they used and time they engaged in the specific application prior to bedtime. Results: Among the different main categories, bedtime procrastinators spent significantly more time on communication and leisure prior to bedtime. In addition, the correlation between depression and amount of time spent watching movie/television/video, and between insomnia severity and time spent communicating through cellphone messenger service were significant. Conclusions The results of this study provide insight into which smartphone applications bedtime procrastinators spend the most time prior to bedtime. The results suggest that the main functions of using their cell phone prior to bedtime are for entertainment and social interaction.