• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.46-51
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• 1999

Objectives: Patients with premenstrual dysphoric disorder(or PMDD) have impairments of the social, occupational or academic function due to psychological or somatic symptoms, which have the characteristic pattern of symptom exacerbation in the week before menses begin and remission shortly after the onset of menses. In the chronobiological view, many researchers have assumed that the etiology of PMDD is the advanced circadian rhythm. It has been suggested that light has a therapeutic effect on PMDD, because evening light results in phase delay of circadian rhythm through the biochemical changes including melatonin. Methods: The authors investigated the therapeutic effect of light therapy on four patients with prospectively diagnosed PMDD by DSM-IV criteria using clinical psychiatric interview, Premenstrual Assessment Form(PAF) and Daily Rating Form(or DRF). In the evening(6:30pm-8:00pm), the 2,500 lux light administered for seven consecutive days during the symptomatic late luteal phase of menstrual cycle. Beck Depression Inventory(or BDI), Hamilton Rating Scale for Depression(or HAM-D), Spielberg State Anxiety Inventory(or SA), and DRF were evaluated before and after seven days of light therapy. Results: Premenstrual symptoms of PMDD could be effectively treated with the evening bright light therapy, especially in PMDD patients with atypical symptoms. In addition, the light therapy seemed to more effective on the psychologic symptoms than the somatic symptoms of PMDD. There was no significant side-effect of light therapy, except the transient and mild eye-strain in one case. Conclusions: In spite of the results of limited data from our clinical trial, the authors suggest that the potential use of light therapy as an alternative to the pharmacological management of patients with PMDD.

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.52-58
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• 2001

Objectives: An Increased level of psychophysiologic arousal and diminished physiologic flexibility would be observed in patients with panic disorder compared with a normal control group. We investigated the differences of psychophysiologic response between patients with panic disorder and normal control to examine this hypothesis. Methods: Ten Korean patients with panic disorder who met the diagnostic criteria of DSM-IV were compared with 10 normal healthy subjects. In psychological assessment, levels of anxiety and depression were evaluated by State-Trait Anxiety Inventory, Beck's Depression Inventory and Hamilton Rating Scale For Anxiety and Depression. Heart rate, respiration rate, electrodermal response, and electromyographic activity were measured by biofeedback system (J & J I-330 model) to determine psychophysiologic responses on autonomic nervous system. Stressful tasks included mental arithmetic, video game, hyperventilation, and talking about a stressful event. Psychophysiologic responses were measured according to the following procedures : baseline(3 min)-mental arithmetic (3 min)-rest (3 min)-video game (3 min)-rest (3 min)-hyperventilation (3 min)-rest (3 min)-talking about a stressful event (3 min). Results: The baseline level of anxiety and depression, electrodermal response (p=.017), electromyographic activity (p=.047) and heart rate (p=.049) of patients with panic disorder were significantly higher than those of the normal subject group. In electrodermal response, patient group had significantly higher startle response than the control group during hyperventilation (p=.001). Startle and recovery responses of heart rate in the patient group were significantly lower than responses in the control group during mental arithmetic (p=.007, p=.002). In electrodermal response of the patient group, startle response was significantly higher than recovery response during mental arithmetic (p=.000) and video game task (p=.021). Recovery response was significantly higher than startle response in respiratory response during hyperventilation. Conclusion: The results showed that patients with panic disorder had higher autonomic arousal than the control group, but the physiologic flexibility was variable. We suggest that it is helpful for treatment of panic disorder to decrease the level of autonomic arousal and to recover the physiologic flexibility in certain stressful event.

• Sleep Medicine and Psychophysiology
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• v.25 no.1
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• pp.15-20
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• 2018

Objectives: This study was designed to assess the change of heart rate variability (HRV) at resting, upright, and psychological stress states in depressive disorder patients. Methods: HRV was measured at resting, upright, and psychological stress states in 62 depressive disorder patients. We used visual analogue scale (VAS) score to assess tension and stress severity. Beck depression inventory (BDI) and state trait anxiety inventories I and II (STAI-I and II) were used to assess depression and anxiety severity, respectively. Differences between HRV indices and VAS score were evaluated using paired t-tests. Gender difference analysis was conducted with ANCOVA. Results: SDNN (standard deviation of normal to normal intervals), LF/HF (low frequency/high frequency), and VLF (very low frequency) were significantly increased, while NN50 and pNN50 were significantly decreased in the upright position compared to resting state. SDNN, RMSSD (root mean square of the differences of successive normal to normal intervals), and VLF were significantly increased, while pNN50 was significantly decreased in the psychological stress state compared to resting state. SDNN, NN50, and pNN50 were significantly lower in an upright position compared to a state of psychological stress, and LF, HF, and LF/HF showed no significant differences Conclusion: The LF/HF ratio was significantly increased after physical stress in depressive disorder. However, the LF/HF ratio was not significantly increased after psychological stress, and the change in LF/HF ratio after physical stress and psychological stress did not significantly differ from each other. Significant increase in SDNN, NN50, and pNN50 in an upright posture compared to psychological stress suggests that depressive patients react more sensitively to physical stress than psychological stress.

• Sleep Medicine and Psychophysiology
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• v.5 no.1
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• pp.71-79
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• 1998

Objectives : This study was to evaluate sleep patterns and daytime sleepiness resulting from rotating shiftwork. The authors, also, tried to find out the relationship between the severity of daytime sleepiness and personality factors. Methods : The subjects consisted of 41 female rotating shiftwork nurses and the control group consisted of 39 female day timeworkers. All of them completed the Sleep questionnaire of Korea University Sleep Disorder Clinic, the Epworth Sleepiness Scale(ESS), the 16 Personality Factors(16PF), the Beck Depression Inventory(BDI) and the State Trait Anxiety Inventory(STAI). Multiple regression analysis of 16PF of the rotating shiftwork nurses was done to find out possible predictors of the severity of daytime sleepiness. Results : The mean duration of deprived sleep due to rotating shiftwork was $64.26\;{\pm}\;14.54\;min$. The frequency of sleep difficulty($1.24\;{\pm}\;1.17\;day/week$ vs $0.67\;{\pm}\;1.31\;day/week$, p < 0.05), time needed to fall asleep($103.05\;{\pm}\;73.48\;min$. vs $70.00\;{\pm}\;60.08\;min$, p < 0.05), sleep duration when having some difficulties in sleep ($204.25\;{\pm}\;79.90\;min$. vs $280.44\;{\pm}\;111.59\;min$., p < 0.001), recent changes in energy($x^2\;=\;4.16$, p < 0.05), worrying about sleep($x^2\;=\;11.08$, p < 0.05), and taking naps($x^2\;=\;4.98$, p < 0.05) showed significant differences between rotating shiftworkers and normal controls. The ESS socre of shiftworkers ($8.68\;{\pm}\;3.04$) was greater than that of normal controls ($6.86\;{\pm}\;3.04$)(p < 0.01). Personality factors such as C factor($R^2\;=0.283$), I factor($R^2\;=0.358$) and G factor($R^2\;=0.470$) were related with the severity of the daytime sleepiness(p < 0.001). Conclusions : The rotating shiftwork nurses had more difficulties in sleep such as having difficulties in falling asleep and in maintaining sleep, and showed lowered energy, decreased senses of well-being and so on. The rotating shiftwork nurses experienced more severe daytime sleepiness than controls did. Personality factors, such as C factor, I factor, and G factor of 16PF were suggested to be useful for predicting the severity of daytime sleepiness resulting from rotating shiftwork.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.38-45
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• 1999

Objectives: We explored the characteristics of physiological variables such as electrodermal response(EDR) and electromyography(EMG) in patients with insomnia, panic disorder, and other anxiety disorders. we aimed to decide the minimum sessions in biofeedback treatment to make the treatment effective and examine the effects of long-term biofeedback treatment by measuring the physiological variables. Methods: Thirty seven outpatients who received biofeedback treatment were divided into 3 groups according to the number of biofeedback sessions(patients who received 4-5 sessions, who received 6-9 sessions, and who received more than 10 sessions). We measured mean and delta values of EDR and EMG levels, and the Hamilton Anxiety Rating Scale(HARS), and Slef-Relaxation Inventory(SRI) in all patients. Data were analyzed by t-test and repeated measures analysis of variance. Results: The mean and delta values of EDR and EMG levels were not different among the 3 groups during the first 4 biofeedback sessions. However, patients who received more than 10 biofeedback sessions had higher baseline mean EDR value(F=2.233, p=0.036) in the first session, compared with other patients. In patients who received more than 10 biofeedback sessions, mean EDR was significantly reduced after $5^{th}$ session(F=10.41, p<0.01). They showed significant improvement in SRI scores at 12th biofeedback session(t=2.726, p<0.05) and in HARS scores at $6^{th}$(t=3.10, p<0.05) and $12^{th}$ biofeedback session(t=10.93, p<0.001). Conclusions: Wesuggest that patients should receive more than 5 biofeedback sessions to experience internal cues and get a good clinical response to biofeedback treatment.

• Sleep Medicine and Psychophysiology
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• v.19 no.1
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• pp.27-34
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• 2012

Objectives: The analysis of heart rate variability (HRV) is a useful non-invasive tool to investigate the autonomic nerve function. Previous studies on the relationship between HRV and depression have been reported controversial results. Similarly, the correlation between the serum lipids and depression is debatable. The purpose of this study is to examine the relationship between heart rate variability, lipid profile and depression. Methods: A total of 42 patients with major depressive disorder (MDD) and 32 age and sex-matched normal subjects who had no previous history of major medical and mental illnesses were recruited for this study. A structured-interview was used to assess the general characteristics and psychiatric illness. HRV measures were assessed by time-domain and frequency-domain analyses. Psychological symptoms were measured using the Hamilton rating scale for anxiety (HAM-A), Hamilton rating scale for depression (HAM-D). In addition, the evaluation for lipid profile was performed by blood test. Results: In serum lipid profile test, MDD group showed higher cholesterol ($197.68{\pm}42.94$ mg/dL vs. $176.85{\pm}34.68$ mg/dL, p=0.044), TG ($139.45{\pm}92.54$ mg/dL vs. $91.4{\pm}65.68$ mg/dL, p=0.018), LDL ($130.03{\pm}33.18$ vs. $106.62{\pm}27.08$, p=0.004) level than normal control group. In HRV time domain analyses, the standard deviation of the NN interval (SDNN) was decreased in MDD group than normal control group, but was not significant ($32.82{\pm}14.33$ ms vs. $40.36{\pm}21.40$ms, p=0.078). ApEn (Approximate Entrophy) was significantly increased in MDD group than normal control group ($1.13{\pm}0.11$ vs. $0.91{\pm}0.18$, p<0.001). ApEn was correlated with LDL level (r=0.277, p=0.028), HAM-D scores (r=0.534, p<0.001) and HAM-A scores (r=0.470, p<0.001). Conclusions: MDD patients showed increased ApEn, one of the HRV measurement. And this ApEn was correlated with LDL, HAM-D and HAM-A scores. In this study, the analysis of ApEn would be a useful test of MDD.

• Sleep Medicine and Psychophysiology
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• v.24 no.1
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• pp.46-54
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• 2017

Objectives: Domestic violence is related to many psychiatric diseases, such as depression, anxiety disorder, and PTSD. Heart rate variability (HRV) is an index of autonomic control of the heart and is related to cardiovascular and emotional disorders. Although there have been some studies on the effects of domestic violence on women's mental health, relatively little information is available on HRV in this population. The aim of this study is to investigate demographic data, psychological features, and HRV in female victims of domestic violence and difference between Korean and foreign female victims. Methods: A total of 210 female victims of domestic violence (166 Korean women and 44 foreign women) were recruited for this study. Psychological symptoms were measured using the Hamilton Rating Scale for Anxiety (HAM-A), Hamilton Rating Scale for Depression (HAM-D), and Impact of Event Scale-Revised (IES-R). HRV measures were assessed by time-domain and frequency-domain analyses. Results: The mean score of HAM-A was 13.81, that of HAM-D was 12.92, and that of IES-R was 33.61 ; there were no significant differences between Korean and foreign women in these measures. In HRV time domain analyses, approximate entropy (ApEn) was significantly increased in foreign women compared to the Korean women. The square root of the mean of the sum of the squares of differences between adjacent NN intervals (RMSSD) was significantly decreased in foreign women compared to Korean women. There were no significant differences in the other HRV variables between Korean and foreign women. Conclusion: Female victims of domestic violence in Korea are associated with depression, anxiety, and PTSD symptoms. The physiologic factors of a female victim's nationality could be related to higher ApEn and lower RMSSD in foreign female victims. These findings have important implications for future study to study the relationships among ethnic and environmental factors and HRV variables.