• Research in Community and Public Health Nursing
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• v.33 no.3
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• pp.279-289
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• 2022

Purpose: This is a descriptive correlation study to confirm the effect of stress and anxiety caused by COVID-19 on the quality of life of small business owners in an area under environment of COVID-19. Methods: The participants were 150 small business owners in an area. The collected data were analyzed by descriptive statistics, an independent t-test, a one-way ANOVA, Pearson's correlation coefficients, and multiple regression with the SPSS 25.0 Program. Results: The stress of small business owners averaged 3.67±0.65 out of 4 points, anxiety of COVID-19 was 2.65±0.52, and quality of life was 75.61±20.26 out of 130 points. The quality of life showed a significant negative correlation with 'fear of infection' (r=-.42, p<.001), 'difficulties caused by social distancing' (r=-.49, p<.001) in the stress subdomain, and anxiety (r=-.61, p<.001). On the other hand, stress, 'fear of infection' (r=.50, p<.001), 'difficulties caused by social distancing' (r=.60 p<.001), 'anger against others' (r=.35, p<.001) and anxiety showed positive correlation. Factors affecting the quality of life of the subjects were 'fear of infection' in the stress subdomain (β=-.23, p=.003), anxiety (β=-.45, p<.001), and residential area (J zone) (β=-.16, p=.030). These factors explained 47.0% of the variance. Conclusion: In order to enhance the quality of life of small business owners in an area, it is required to reduce stress and anxiety. In addition, it is necessary to prepare an intervention program that can reduce stress and anxiety of small business owners.

• Asian Journal for Public Opinion Research
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• v.12 no.1
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• pp.53-74
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• 2024

The proliferation of health misinformation gained momentum amidst the outbreak of the novel coronavirus disease 2019 (COVID-19). People stuck in their homes, without work pressure, regardless of health concerns towards personal, family, or peer groups, consistently demanded information. People became engaged with misinformation while attempting to find health information content. This study used the content analysis method and analyzed 1,154 misinformation stories from four prominent signatories of the International Fact-Checking Network during the pandemic. The study finds the five main categories of misinformation related to the COVID-19 pandemic. These are 1) the severity of the virus, 2) cure, prevention, and treatment, 3) myths and rumors about vaccines, 4) health authorities' guidelines, and 5) personal and social impacts. Various sub-categories supported the content characteristics of these categories. The study also analyzed the emotional valence of health misinformation. It was found that misinformation containing negative sentiments got higher engagement during the pandemic. Positive and neutral sentiment misinformation has less reach. Surprise, fear, and anger/aggressive emotions highly affected people during the pandemic; in general, people and social media users warning people to safeguard themselves from COVID-19 and creating a confusing state were found as the primary motivation behind the propagation of misinformation. The present study offers valuable perspectives on the mechanisms underlying the spread of health-related misinformation amidst the COVID-19 outbreak. It highlights the significance of discerning the accuracy of information and the feelings it conveys in minimizing the adverse effects on the well-being of public health.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.146-160
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• 2024

Background and Purpose: The emotions of people at various stages of dementia need to be effectively utilized for prevention, early intervention, and care planning. With technology available for understanding and addressing the emotional needs of people, this study aims to develop speech emotion recognition (SER) technology to classify emotions for people at high risk of dementia. Methods: Speech samples from people at high risk of dementia were categorized into distinct emotions via human auditory assessment, the outcomes of which were annotated for guided deep-learning method. The architecture incorporated convolutional neural network, long short-term memory, attention layers, and Wav2Vec2, a novel feature extractor to develop automated speech-emotion recognition. Results: Twenty-seven kinds of Emotions were found in the speech of the participants. These emotions were grouped into 6 detailed emotions: happiness, interest, sadness, frustration, anger, and neutrality, and further into 3 basic emotions: positive, negative, and neutral. To improve algorithmic performance, multiple learning approaches were applied using different data sources-voice and text-and varying the number of emotions. Ultimately, a 2-stage algorithm-initial text-based classification followed by voice-based analysis-achieved the highest accuracy, reaching 70%. Conclusions: The diverse emotions identified in this study were attributed to the characteristics of the participants and the method of data collection. The speech of people at high risk of dementia to companion robots also explains the relatively low performance of the SER algorithm. Accordingly, this study suggests the systematic and comprehensive construction of a dataset from people with dementia.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.51-66
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• 2018

As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.4
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• pp.121-138
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• 2017

As information users seek multimedia with a wide variety of information needs, information environments for multimedia have been developed drastically. More specifically, as seeking multimedia with emotional access points has been popular, the needs for indexing in terms of abstract concepts including emotions have grown. This study aims to analyze the index terms extracted from Getty Image Bank. Five basic emotion terms, which are sadness, love, horror, happiness, anger, were used when collected the indexing terms. A total 22,675 index terms were used for this study. The data are three sets; entire emotion, positive emotion, and negative emotion. For these three data sets, co-word occurrence matrices were created and visualized in weighted network with PNNC clusters. The entire emotion network demonstrates three clusters and 20 sub-clusters. On the other hand, positive emotion network and negative emotion network show 10 clusters, respectively. The results point out three elements for next generation of multimedia retrieval: (1) the analysis on index terms for emotions shown in people on image, (2) the relationship between connotative term and denotative term and possibility for inferring connotative terms from denotative terms using the relationship, and (3) the significance of thesaurus on connotative term in order to expand related terms or synonyms for better access points.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.117-131
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• 2014

This study aims to explore the reexperience of trauma caused by experience of discrimination and stigma from South Korean. For this purpose of this study, focus group interview methods are used. The participants are five women who escaped from North Korea and they were from 20s to 50s. From the outcomes of this study, I find out that they had experienced to put in prison, to let arrest to let human traffic, and sexual or physical assault. Now they have PTSD(Post Trauma Stress Symptom) of nightmare related with past trauma, avoidance of interpersonal relationships and similar situations, and retrospection and memorization of negative experiences. In that situation, they also have experienced discrimination caused by lack of understanding of their suffering in South Korea. And almost of them suffer from poor situation economically and physically. Participants regret their entry to South Korea and perceive that their hope has gone. And they have anger of Korean's discrimination and stigma and they feel suicide impulse after experiencing very difficult situation. These negative experiences affect their PTSD and make reemergence of trauma experience. In conclusion, the outcomes of this study are discussed and I proposed the practical suggestions which have affected decreasing the PTSD.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.1-23
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• 2011

The contextual subjective well-being (SWB) of context-aware system users can be very helpful in recommending relevant mental health services, especially for those who struggle with mental illness due to a metabolic syndrome or melancholia. Self-surveying measuring or auto-sensing methods have been suggested to monitor users' SWB. However, self-surveying measuring method is not inappropriate for a context-aware service due to requesting personal data in a manual and hence obtrusive manner. Moreover, auto-sensing methods still suffer from accuracy problem to be applied in mental health services. Hence, the purpose of this paper is to propose a contextual SWB estimation method to estimate the user's mental health in unobtrusive and accurate manners. This method is timely in that it acquires context data from the user's literal responses, which expose their temporal feeling. In particular, we developed a measuring method based on exposed feeling verbs and degree adverbs in chat and other text-based communications which show anger or negative feelings. Based on the proposed contextual SWB degree estimation method, we developed an idea of well-being life care recommendation. From the experiment with actual drivers, we demonstrated that the proposed method accurately estimate the user's degree of negative feelings even though it does not require a self-survey.

• Journal of muscle and joint health
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• v.6 no.2
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• pp.226-241
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• 1999

This study was undertaken to find out the causal perception of rheumatoid arthritis patients, and to understand the typology. The Q-population consisted of 236 statements of causal perception were collected. Thirty eight Q-samples of causal perception were selected. The P-sample for this study were made up of 28 first visiting female rheumatoid arthritis patients from a rheumatoid arthritis specialty hospital. Each respondent responded Q-set of causal perception according to 9-point scale. The result of Q-sorting were coded and analyzed using QUANL PC program. 1) Typological Observation on Causal Perception (1) Physical Fatigue Type : Type 1 perceived that the illness occurred due to excessive work requiring physical labor or strain that had occurred from not resting after excessive physical labor, therefore, thinking the origin of the illness was from physical strain. (2) Physical origin Type : Type 2 perceived that the major cause for the illness is not only excessive physical labour but also fecundity and old age. (3) Causality to Environment Type : Type 3 perceived that rheumatoid arthritis occurred from injury to the joints or bad and humid weather. (4) Conscience of Guilty Type : Type 4 consisted of people with guilty conscience for lack of religious commitment. They perceived that the illness was a punishment from God for not praying or because of bad luck. (5) Rationally Perceiving Type : People who belong in type 5 perceived the cause of illness in light of scientific facts such as genetics, unbalanced diet or lack of exercise. (6) Psychological Stress Type : People who belong in type 6 believed that excessive stress was the cause of the illness. 2) Emotions of Rheumatoid arthritis patients Rheumatoid arthritis patients' positive emotions included determination, courage, coping, acceptance, hope, and adoption ; and their negative emotions were prostration, worry, stupor, conflicts, grievance, giving-up, resignation, depression, loss, solitariness, fear, anxiety, avoidance, anger and loneliness. Rheumatoid arthritis patients experience different level of emotions from their suffering experience from the severe pains. Rheumatoid arthritis patients also experience negative emotions when they could not perform self-care and lose their self-esteem from painful suffering ; however, they regain positive emotions when they recover from pain with the use of drugs, physical therapy or exercise. Their emotional states are closely connected to level of and presence of pain.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.269-279
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• 2019

The purpose of this study was to investigate if a positive psychological-based music therapy program for gambling addicts' families, causes explicit or implicit attitude change towards gambling addicts. The study focused on families with gambling addicts, who use counseling centers for gambling addiction, or participate in GAM-ANON (GA). The experimental group (n=11) participated in 8 sessions of a positive psychology-based group music therapy program, and the control group (n=8) participated in 8 sessions of personal counseling, or GA family gatherings. To confirm treatment effectiveness, the attitude towards the family relationship, was measured by the explicit (Family Relation Scale) and Implicit Association Task (IAT) methods. Additionally, change in emotions including and anger (PANAS, HBDIS), was measured. Results of the study showed that positive emotions increased significantly, in the positive psychotherapy-based music therapy group compared, to the control group. However, in the treatment group with implicit attitudes, the rate of association of negative words with families accelerated significantly, suggesting that gambling addicts' families may have higher negative emotions. For the future, we discussed the necessity of providing a treatment program, that can directly lead to changes in attitudes of family members of gambling addicts.

• Phonetics and Speech Sciences
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• v.13 no.4
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• pp.101-114
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• 2021

The purpose of this study was to investigate the temperament characteristics associated with stuttering subtypes (persistent and recovered) over time and the relationship between those characteristics and stuttering severity. This four-year longitudinal study covered 41 preschool children who stutter (CWS) and 30 preschool children who do not stutter (the CWNS group). At the final visit, 27 CWS were classified as the Recovered group and 14 CWS were classified as the Persistent group. Using the Children's Behavior Questionnaire-Short Form, each participant's temperament characteristics were measured twice: at one year and two years after the initial visit. The three subscale scores (Extraversion, Negative Affectivity, and Effortful Control) and the 15 component scores were analyzed, and they were used for between-group and between-visit comparisons. The Persistent group showed a significantly higher Negative Affectivity subscale score at every visit than the Recovered and CWNS groups. Within this subscale, significant group differences were found in the 'Fear' and 'Anger/Frustration' components, demonstrating that the Persistent group scored higher than the Recovered and CWNS groups. There was no significant correlation between the subscale and component scores and the stuttering severity scores within the Persistent group at any visit. These results support the proposition that these two stuttering subtypes have different temperament characteristics; they also imply that temperament might be influenced by stuttering experience over time.