• Title, Summary, Keyword: mood

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Design and Methods of the Mood Disorder Cohort Research Consortium (MDCRC) Study

  • Cho, Chul-Hyun;Ahn, Yong-Min;Kim, Se Joo;Ha, Tae Hyun;Jeon, Hong Jin;Cha, Boseok;Moon, Eunsoo;Park, Dong Yeon;Baek, Ji Hyun;Kang, Hee-Ju;Ryu, Vin;An, Hyonggin;Lee, Heon-Jeong
    • Psychiatry investigation
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    • v.14 no.1
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    • pp.100-106
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    • 2017
  • The Mood Disorder Cohort Research Consortium (MDCRC) study is designed as a naturalistic observational prospective cohort study for early-onset mood disorders (major depressive disorders, bipolar disorders type 1 and 2) in South Korea. The study subjects consist of two populations: 1) patients with mood disorders under 25 years old and 2) patients with mood disorders within 2 years of treatment under 35 years old. After successful screening, the subjects are evaluated using baseline assessments and serial follow-up assessments at 3-month intervals. Between the follow-up assessments, subjects are dictated to check their own daily mood status before bedtime using the eMood chart application or a paper mood diary. At the regular visits every 3 months, inter-visit assessments are evaluated based on daily mood charts and interviews with patients. In addition to the daily mood chart, sleep quality, inter-visit major and minor mood episodes, stressful life events, and medical usage pattern with medical expenses are also assessed. Genomic DNA from blood is obtained for genomic analyses. From the MDCRC study, the clinical course, prognosis, and related factors of early-onset mood disorders can be clarified. The MDCRC is also able to facilitate translational research for mood disorders and provide a resource for the convergence study of mood disorders.

Brainwave-based Mood Classification Using Regularized Common Spatial Pattern Filter

  • Shin, Saim;Jang, Sei-Jin;Lee, Donghyun;Park, Unsang;Kim, Ji-Hwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.2
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    • pp.807-824
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    • 2016
  • In this paper, a method of mood classification based on user brainwaves is proposed for real-time application in commercial services. Unlike conventional mood analyzing systems, the proposed method focuses on classifying real-time user moods by analyzing the user's brainwaves. Applying brainwave-related research in commercial services requires two elements - robust performance and comfortable fit of. This paper proposes a filter based on Regularized Common Spatial Patterns (RCSP) and presents its use in the implementation of mood classification for a music service via a wireless consumer electroencephalography (EEG) device that has only 14 pins. Despite the use of fewer pins, the proposed system demonstrates approximately 10% point higher accuracy in mood classification, using the same dataset, compared to one of the best EEG-based mood-classification systems using a skullcap with 32 pins (EU FP7 PetaMedia project). This paper confirms the commercial viability of brainwave-based mood-classification technology. To analyze the improvements of the system, the changes of feature variations after applying RCSP filters and performance variations between users are also investigated. Furthermore, as a prototype service, this paper introduces a mood-based music list management system called MyMusicShuffler based on the proposed mood-classification method.

The Interaction between Personality Characteristics and Mood States in Media Contents Selection

  • Cho, Seungho;Hur, Junsoo
    • International Journal of Contents
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    • v.14 no.4
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    • pp.51-56
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    • 2018
  • This study was conducted to explore the relationship between personality characteristics and mood in the selection of media content. Using meta-analysis, this study analyzed past studies regarding media content selection in television program. The results of this research showed that the preference of a given media content would depend on the viewer's mood, personality characteristics and the interaction between personality characteristics and mood states. The secondary data of television programs supported the association.

Relationships of Mood Disturbance, Symptom Experience, and Attentional Function in Women with Breast Cancer Based upon the Theory of Unpleasant Symptoms

  • Lee Eun-Hyun
    • Journal of Korean Academy of Nursing
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    • v.35 no.4
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    • pp.728-736
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    • 2005
  • Purpose. The purpose of this study was to identify direct, mediating, and moderating relationships of mood disturbance, symptom experience, and attentional function in Korean women with breast cancer based upon a middle-range theory of unpleasant symptoms. Methods. This study used a cross-sectional, correlational design. A convenience sample of 125 women receiving chemotherapy for breast cancer was recruited from a university hospital in South Korea. The women completed questionnaires on mood disturbance, symptom experience, and attentional function using the Linear Analogue Self-Assessment Scale, the Symptom Experience Scale, and the Attentional Function Index, respectively. Results. Each mood disturbance and symptom experience showed a significant relationship with attentional function. Symptom experience did not act as a mediator between mood disturbance and attentional function, but it did act as a moderator: patients with a higher level of mood disturbance exhibited a lower level of attentional function when their symptoms were at the level of medium, but not when their symptoms were either high or low. Conclusion. This suggests that clinical interventions for attenuating the influence of mood disturbance on attentional function may be effective only in women experiencing medium level of symptoms.

The Changes of the Circadian Rhythm of Mood in Shift Worker (교대근무에 따른 기분의 Circadian Rhythm 변화)

  • 고성희;김명애
    • Journal of Korean Academy of Nursing
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    • v.24 no.2
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    • pp.175-189
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    • 1994
  • This study examined the daily rhythmic patterns of mood in shift workers. Ten rotating shift nurses (shift worker group) were matched with ten non-rotating student nurses (non - shift worker group) working under the same conditions at University Hospital. The subjects completed the Mood Adjective Checkist (MAC) every two or three hours from 6AM to 9-11 PM for six consecutive days. The MAC was constructed by Mansour and conversed the mood factors of Anger - Depression. Happiness, Mental, and Social. These data were analyzed by using Cosinor method. The results are summarized as follows : 1. There was no difference in mean scores for Anger - Depression, Happiness, Mental, and Social mood rhythm between the shift workers and the non - shift workers. 2. There was no difference in the amplitude of Anger - Depression, Happiness and Social mood between the two groups, but the shift workers had a higher amplitude of Mental mood. 3. The acrophases of the Anger - Depression mood were between 1:28 and 2:05, and those of Happiness, Social, and Mental mood were between 12:5 and 15:03 for both groups. There were no differences between the groups. 4. The number of the subjects with statistically significant mean cosinor rhythms for Anger-De-pression and Mental moods were higher in the shift workers than in the non-shift workers, but there were no differences between the shift workers and the non-shift workers in those of Happiness and Mental mood. This study showed that the mod manifested circadian periodicities, and a rapidly rotating shift system did not changed the circadian rhythm of mood. It is expected that this study will facilitate a better understanding of circadian rhythm in mood in the shiftworkers.

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Detection of Music Mood for Context-aware Music Recommendation (상황인지 음악추천을 위한 음악 분위기 검출)

  • Lee, Jong-In;Yeo, Dong-Gyu;Kim, Byeong-Man
    • The KIPS Transactions:PartB
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    • v.17B no.4
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    • pp.263-274
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    • 2010
  • To provide context-aware music recommendation service, first of all, we need to catch music mood that a user prefers depending on his situation or context. Among various music characteristics, music mood has a close relation with people‘s emotion. Based on this relationship, some researchers have studied on music mood detection, where they manually select a representative segment of music and classify its mood. Although such approaches show good performance on music mood classification, it's difficult to apply them to new music due to the manual intervention. Moreover, it is more difficult to detect music mood because the mood usually varies with time. To cope with these problems, this paper presents an automatic method to classify the music mood. First, a whole music is segmented into several groups that have similar characteristics by structural information. Then, the mood of each segments is detected, where each individual's preference on mood is modelled by regression based on Thayer's two-dimensional mood model. Experimental results show that the proposed method achieves 80% or higher accuracy.

An Empirical Study on Factor Associated with Mood Disorders in Elderly: Focusing on the Influence of Community Characteristics (노인 기분장애 영향요인에 관한 실증적 연구: 지역사회 특성의 영향을 중심으로)

  • Chang, Miseung;Shim, Ik Sup
    • Health Policy and Management
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    • v.27 no.2
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    • pp.177-185
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    • 2017
  • Background: The mental problems of the elderly are at issue as a serious social phenomenon. The purpose of this study is to identify risk factors affecting the mood disorders of the elderly. Methods: The subjects were 1,779,236 aged ${\geq}65$ and participated in health screening. Dependent variable was mood disorders. Independent variables were consisted of community level (regional deprivation index and healthcare resources) and individual level (sex, age, insurance type, disability, smoking, alcohol, physical activity, body mass index, and healthcare utilization). Multilevel logistic regression was performed. Results: At the individual level, women, employed insured, severely disabled people, heavy alcohol drinkers, high-intensity physical activity, body mass index, and patients who had chronic disease and severe disease were significantly associated with mood disorders. As the age has increased, it has let increase of mood disorders. At the community level, as the regional deprivation index has increased by 1, mood disorders has been increased by 1.005 times. The intra-class coefficient was 7.04%. Conclusion: We found individual and community level factors are associated with mood disorders. Systematic approach is essential to reduce mood disorders.

Body Mass Index, Body Weight Perception, and Depressed Mood in Korean Adolescents

  • Lim, Yooli;Kim, Bongseog
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.28 no.1
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    • pp.31-37
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    • 2017
  • Objectives: We examined the relationships between the body mass index, body weight perception, and depressed mood in a nationally representative sample of Korean adolescents. Methods: We analyzed the data from the 2013 Korean Youth Risk Behavior Web-based Survey and evaluated the relationships between the body mass index, body weight perception, and depressed mood by gender (36655 boys and 35780 girls). Results: For boys, a low body mass index and perceiving oneself as underweight were related to depressed mood. For girls, both low and high body mass indices were negatively related to depressed mood. In addition, self-perceptions of being underweight or overweight were positively related to depressed mood. Body weight perception was not a significant mediator in the relationship between body mass index and depressed mood. Conclusion: These results suggest that both body mass index and body weight perception significantly contribute to Korean adolescents' depressed mood. Thus, research and clinical attention needs to be given to underweight as well as overweight adolescents, because those who perceive their weight as not normal are at risk for depression.

A Study on Negation Handling and Term Weighting Schemes and Their Effects on Mood-based Text Classification (감정 기반 블로그 문서 분류를 위한 부정어 처리 및 단어 가중치 적용 기법의 효과에 대한 연구)

  • Jung, Yu-Chul;Choi, Yoon-Jung;Myaeng, Sung-Hyon
    • Korean Journal of Cognitive Science
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    • v.19 no.4
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    • pp.477-497
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    • 2008
  • Mood classification of blog text is an interesting problem, with a potential for a variety of services involving the Web. This paper introduces an approach to mood classification enhancements through the normalized negation n-grams which contain mood clues and corpus-specific term weighting(CSTW). We've done experiments on blog texts with two different classification methods: Enhanced Mood Flow Analysis(EMFA) and Support Vector Machine based Mood Classification(SVMMC). It proves that the normalized negation n-gram method is quite effective in dealing with negations and gave gradual improvements in mood classification with EMF A. From the selection of CSTW, we noticed that the appropriate weighting scheme is important for supporting adequate levels of mood classification performance because it outperforms the result of TF*IDF and TF.

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Moderating effect of music characteristics on the relationship between consumer mood and attitude in the online shopping mall (온라인 쇼핑몰 소비자의 기분-태도 관계에 영향을 미치는 배경음악 특성의 조절효과)

  • Choi, Soojin;Yoh, Eunah
    • The Research Journal of the Costume Culture
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    • v.23 no.5
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    • pp.793-806
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    • 2015
  • This study is to explore the effect of music characteristics (i.e., likeliness and familiarity of music) on the relationship between mood and attitude toward the product in the online shopping mall selling hand-made shoes. A total of 319 consumers participated in experiments with online shopping mall stimuli with a variety of background music. In results, consumer mood positively affected attitude toward the hand-made shoe products in the online shopping mall under background music. A moderating effect of music likeliness was found in the relationship between mood and product attitude, indicating that mood more strongly affected product attitude under more liked music than under less liked music. When consumers are listening to more liked music and are in good mood, they may build their attitudes toward products independently from their mood, whereas they may build positive attitude under good mood versus negative attitudes under bad mood if they are listening to less liked music. A moderating effect of music familiarity was not found in the relationship between mood and product attitude. Based on results, it was confirmed that the S-O-R model could be applied to explain the effect of background music on consumer responses in online shopping malls. Marketers may be able to select and adjust the likeliness and familiarity of background music to better serve consumers in diverse shopping conditions, referring to the study findings.