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Article ; Online: Investigating psychological and motivational predictors of problematic smartphone use among Smartphone-based Social Networking Service (SNS) users.

Kwak, Min-Jung / Kim, Dai-Jin

2023 Volume 18, Page(s) 100506

Abstract: Given that the active use of certain smartphone applications is associate with problematic smartphone use, it has been proposed that certain smartphone applications are more addictive than others, such as Social Networking Services (SNS). Still, studies ... ...

Abstract	Given that the active use of certain smartphone applications is associate with problematic smartphone use, it has been proposed that certain smartphone applications are more addictive than others, such as Social Networking Services (SNS). Still, studies that consider smartphone users' main usage application which are known to influence the users' problematic smartphone use, such as SNS, remain to be explored. Thus, the current study aims to investigate the psychological and motivational predictors of problematic smartphone use in a sample of smartphone-based SNS users whose main device usage is SNS. A series of mean comparison tests and binary logistic regression were performed in this study. Of the 433 smartphone-based SNS users, 218 were male (50.3%) and 215 were female (49.7%). Age of 433 participants ranged from 20 to 40, and mean age was 30.75 (SD = 7.84). 73 participants (16.9%) were sorted into the high-risk problematic smartphone use group and 360 participants (83.1%) were categorized as the normal user group. The finding from binary regression analysis showed that reward responsiveness from the Behavioral Activation System (BAS), a lack of self-control, and anxiety significantly increased the odds of problematic smartphone use of the smartphone-based SNS users. Reward responsiveness was found to be the most powerful predictor. Our findings broaden the existing literature and provide implications to reduce addictive smartphone use relating to smartphone-based SNS usage.
Language	English
Publishing date	2023-06-21
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2831558-3
ISSN	2352-8532 ; 2352-8532
ISSN (online)	2352-8532
ISSN	2352-8532
DOI	10.1016/j.abrep.2023.100506
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The Role of Motivation Systems, Anxiety, and Low Self-Control in Smartphone Addiction among Smartphone-Based Social Networking Service (SNS) Users.

Kwak, Min-Jung / Cho, Hyun / Kim, Dai-Jin

International journal of environmental research and public health

2022 Volume 19, Issue 11

Abstract: Given that Social Networking Service (SNS) has emerged as the most influential platform, which can lead users to addictive smartphone use, it is necessary to investigate which psychological variables lead smartphone-based SNS users to addictive ... ...

Abstract	Given that Social Networking Service (SNS) has emerged as the most influential platform, which can lead users to addictive smartphone use, it is necessary to investigate which psychological variables lead smartphone-based SNS users to addictive smartphone use. Still, studies on the relationship between psychological variables and addictive smartphone use among smartphone-based SNS users remain to be explored. Therefore, this study aims to investigate the role of psychological factors on smartphone addiction proneness (SAP). A total of 433 smartphone-based SNS users were collected from 5003 adults in Korea. Data were analyzed with descriptive statistics, Pearson's correlation coefficients, and path analysis using SPSS 21.0 and AMOS 23.0. The results of a parallel-mediation path analysis demonstrated that Behavioral Inhibition (BIS), Behavioral activation (BAS) drive, anxiety, and low self-control directly influenced SAP, separately. BIS and BAS _drive also had significant indirect effects on SAP through the effect of anxiety. BIS and BAS_fun had significant indirect effects on SAP through the effect of low self-control. The study variables accounted for 38.4 of the total variances of SAP. Thus, when establishing interventions to reduce the users' addictive smartphone use, these interactive relationships of the variables should be considered.
MeSH term(s)	Adult ; Anxiety ; Behavior, Addictive/psychology ; Humans ; Internet Addiction Disorder ; Motivation ; Self-Control/psychology ; Smartphone ; Social Networking
Language	English
Publishing date	2022-06-05
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2175195-X
ISSN	1660-4601 ; 1661-7827
ISSN (online)	1660-4601
ISSN	1661-7827
DOI	10.3390/ijerph19116918
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Book ; Online: DAM-GAN

Cha, Dongmin / Kim, Daijin

Image Inpainting using Dynamic Attention Map based on Fake Texture Detection

2022

Abstract: Deep neural advancements have recently brought remarkable image synthesis performance to the field of image inpainting. The adaptation of generative adversarial networks (GAN) in particular has accelerated significant progress in high-quality image ... ...

Abstract	Deep neural advancements have recently brought remarkable image synthesis performance to the field of image inpainting. The adaptation of generative adversarial networks (GAN) in particular has accelerated significant progress in high-quality image reconstruction. However, although many notable GAN-based networks have been proposed for image inpainting, still pixel artifacts or color inconsistency occur in synthesized images during the generation process, which are usually called fake textures. To reduce pixel inconsistency disorder resulted from fake textures, we introduce a GAN-based model using dynamic attention map (DAM-GAN). Our proposed DAM-GAN concentrates on detecting fake texture and products dynamic attention maps to diminish pixel inconsistency from the feature maps in the generator. Evaluation results on CelebA-HQ and Places2 datasets with other image inpainting approaches show the superiority of our network.
Keywords	Computer Science - Computer Vision and Pattern Recognition ; Electrical Engineering and Systems Science - Image and Video Processing
Subject code	006
Publishing date	2022-04-20
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Weight-based Mask for Domain Adaptation

Lee, Eunseop / Kim, Inhan / Kim, Daijin

2023

Abstract: In computer vision, unsupervised domain adaptation (UDA) is an approach to transferring knowledge from a label-rich source domain to a fully-unlabeled target domain. Conventional UDA approaches have two problems. The first problem is that a class ... ...

Abstract	In computer vision, unsupervised domain adaptation (UDA) is an approach to transferring knowledge from a label-rich source domain to a fully-unlabeled target domain. Conventional UDA approaches have two problems. The first problem is that a class classifier can be biased to the source domain because it is trained using only source samples. The second is that previous approaches align image-level features regardless of foreground and background, although the classifier requires foreground features. To solve these problems, we introduce Weight-based Mask Network (WEMNet) composed of Domain Ignore Module (DIM) and Semantic Enhancement Module (SEM). DIM obtains domain-agnostic feature representations via the weight of the domain discriminator and predicts categories. In addition, SEM obtains class-related feature representations using the classifier weight and focuses on the foreground features for domain adaptation. Extensive experimental results reveal that the proposed WEMNet outperforms the competitive accuracy on representative UDA datasets. Comment: 5 pages, 2 figures, to be published in ICASSP2023
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	004 ; 006
Publishing date	2023-04-22
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Deep Sequence Learning Framework for Action Recognition in Small-Scale Depth Video Dataset.

Bulbul, Mohammad Farhad / Ullah, Amin / Ali, Hazrat / Kim, Daijin

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 18

Abstract: Depth video sequence-based deep models for recognizing human actions are scarce compared to RGB and skeleton video sequences-based models. This scarcity limits the research advancements based on depth data, as training deep models with small-scale data ... ...

Abstract	Depth video sequence-based deep models for recognizing human actions are scarce compared to RGB and skeleton video sequences-based models. This scarcity limits the research advancements based on depth data, as training deep models with small-scale data is challenging. In this work, we propose a sequence classification deep model using depth video data for scenarios when the video data are limited. Unlike summarizing the frame contents of each frame into a single class, our method can directly classify a depth video, i.e., a sequence of depth frames. Firstly, the proposed system transforms an input depth video into three sequences of multi-view temporal motion frames. Together with the three temporal motion sequences, the input depth frame sequence offers a four-stream representation of the input depth action video. Next, the DenseNet121 architecture is employed along with ImageNet pre-trained weights to extract the discriminating frame-level action features of depth and temporal motion frames. The extracted four sets of feature vectors about frames of four streams are fed into four bi-directional (BLSTM) networks. The temporal features are further analyzed through multi-head self-attention (MHSA) to capture multi-view sequence correlations. Finally, the concatenated genre of their outputs is processed through dense layers to classify the input depth video. The experimental results on two small-scale benchmark depth datasets, MSRAction3D and DHA, demonstrate that the proposed framework is efficacious even for insufficient training samples and superior to the existing depth data-based action recognition methods.
MeSH term(s)	Databases, Factual ; Human Activities ; Humans ; Motion ; Neural Networks, Computer ; Skeleton
Language	English
Publishing date	2022-09-09
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22186841
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Article ; Online: Dementia Research Using Healthcare Big Data.

Kim, Hun-Sung / Kim, Dai-Jin

Dementia and neurocognitive disorders

2019 Volume 18, Issue 3, Page(s) 73–76

Language	English
Publishing date	2019-10-01
Publishing country	Korea (South)
Document type	Editorial
ZDB-ID	3015713-4
ISSN	2384-0757 ; 1738-1495
ISSN (online)	2384-0757
ISSN	1738-1495
DOI	10.12779/dnd.2019.18.3.73
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Article: Smart Healthcare Systems and Precision Medicine.

Paik, Soo-Hyun / Kim, Dai-Jin

Advances in experimental medicine and biology

2019 Volume 1192, Page(s) 263–279

Abstract: This article gives an overview of the concept and brain mechanisms of Internet game and smartphone addiction and the applicability of precision medicine and smart healthcare system. Internet game and smartphone addiction are categorized as behavioral ... ...

Abstract	This article gives an overview of the concept and brain mechanisms of Internet game and smartphone addiction and the applicability of precision medicine and smart healthcare system. Internet game and smartphone addiction are categorized as behavioral addictions, which share similar phenomenology and neurobiological underpinnings with substance addictions. Neuroimaging studies revealed the alteration in the functional activity and structure of individuals with Internet game and smartphone addiction, which also can be potent biomarkers. Precision medicine is defined as treatments targeted to the individual patients on the basis of genetic, biomarker, phenotypic or psychosocial characteristics. Recent advances in high-throughput technology and bioinformatics have enabled us to integrate these big data with behavioral data collected from smartphones or other wearable devices. Data collected via smart devices can be transferred to medical institute and integrated in order to diagnose current status precisely and to provide optimal intervention. The feedbacks of intervention are sent back to the medical provider via self-reports or objective measures to evaluate the appropriateness of the intervention. In conclusion, Internet game and smartphone addiction can be diagnosed precisely using high-throughput technology and optimally managed via smart healthcare system.
MeSH term(s)	Behavior, Addictive/diagnosis ; Behavior, Addictive/therapy ; Cognitive Behavioral Therapy/methods ; Delivery of Health Care/methods ; Humans ; Internet ; Mental Disorders/epidemiology ; Neuroimaging ; Precision Medicine ; Smartphone ; Substance-Related Disorders ; Video Games
Language	English
Publishing date	2019-11-08
Publishing country	United States
Document type	Journal Article ; Review
ISSN	2214-8019 ; 0065-2598
ISSN (online)	2214-8019
ISSN	0065-2598
DOI	10.1007/978-981-32-9721-0_13
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Article: The Effect of Stress on Internet Game Addiction Trends in Adults: Mindfulness and Conscientiousness as Mediators.

Choi, Taeyeong / Park, Jae Woo / Kim, Dai-Jin

Psychiatry investigation

2021 Volume 18, Issue 8, Page(s) 779–788

Abstract: Objective: This study examined the mediating effect of mindfulness and consciousness among five factors on the effect of stress on Internet game addiction tendency.: Methods: An online survey was conducted on 400 men and women between their 20s and ... ...

Abstract	Objective: This study examined the mediating effect of mindfulness and consciousness among five factors on the effect of stress on Internet game addiction tendency. Methods: An online survey was conducted on 400 men and women between their 20s and 40s across Korea. The scales used in the study were the Internet game addiction scale based on the DSM-5, Perceived Stress Scale, Mindfulness Scale, and Five-Factor Personality Scale. For data analysis, structural equation modeling was conducted, and Sobel verification was carried out to verify the significance of the mediating effects. Results: The results of the study are as follows: Stress showed a positive correlation with Internet game addiction tendency, mindfulness mediated the effect of stress on Internet game addiction tendency. Conclusion: Of the five personality factors, conscientiousness also mediated the effect of stress on Internet game addiction tendency. This study highlights the need for further research for individuals with game addiction tendency.
Language	English
Publishing date	2021-08-13
Publishing country	Korea (South)
Document type	Journal Article
ZDB-ID	2414364-9
ISSN	1976-3026 ; 1738-3684
ISSN (online)	1976-3026
ISSN	1738-3684
DOI	10.30773/pi.2020.0034
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Article ; Online: Characteristics and Potential Challenges of Digital-Based Interventions for Children and Young People: Scoping Review.

Yun, Jinsoo / Shin, Jaeyong / Lee, Hyerim / Kim, Dai-Jin / Choi, In-Young / Kim, Meelim

Journal of medical Internet research

2023 Volume 25, Page(s) e45465

Abstract: Background: Digital health technologies are becoming increasingly available to children and young people and their families. However, there are no scoping reviews that provide both an overview of the characteristics of digital interventions for children ...

Abstract	Background: Digital health technologies are becoming increasingly available to children and young people and their families. However, there are no scoping reviews that provide both an overview of the characteristics of digital interventions for children and young people and potential challenges to be considered when developing and implementing them. Objective: This study aimed to systematically review scientific publications to identify the current characteristics and potential complications of digital interventions for children and young people. Methods: This scoping review was conducted using the framework of Arksey and O'Malley and adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews. A search of 5 databases (PubMed, Scopus, Embase, MEDLINE, and CINAHL) and Google Scholar was performed for eligible clinical trials published between January 1, 2018, and August 19, 2022. Results: The initial search of the 5 databases yielded 3775 citations; duplicates and those not meeting the inclusion criteria were eliminated. In total, 34 articles were included in the final review and relevant information, such as the descriptive characteristics and potential challenges, were classified. Mental health (26/34, 76%) was the most common target for the digital intervention for children and young people, exceeding physical health (8/34, 24%) by more than 3 times. In addition, a substantial number of digital interventions were dedicated solely to children and young people. Digital interventions for children and young people were more likely to be delivered via computers (17/34, 50%) rather than smartphones (13/34, 38%). More than one-third of the studies (13/34, 38%) applied cognitive behavioral theory as the theory of digital interventions. The duration of the digital intervention for children and young people was more likely to vary depending on the target user rather than the target disease. Intervention components were classified into 5 categories: guidance, task and activity, reminder and monitoring, supportive feedback, and reward system. Potential challenges were subcategorized into ethical, interpersonal, and societal challenges. For ethical challenges, the consent of children and young people or caregivers, potential risk of adverse events, and data privacy issues were considered. For interpersonal challenges, the engagement of children and young people was affected by the preference or barrier of caregivers to participate in studies. For societal challenges, restricted ethnicity in recruitment, limited availability of digital technology, differences in internet use patterns between girls and boys, unified clinical settings, and language barriers were described. Conclusions: We identified potential challenges and provided suggestions about ethical, interpersonal, and societal aspects to consider when developing and deploying digital-based interventions for children and young people. Our findings provide a thorough overview of the published literature and may serve as a comprehensive, informative foundation for the development and implementation of digital-based interventions for children and young people.
MeSH term(s)	Male ; Female ; Humans ; Child ; Adolescent ; Mental Health ; Smartphone
Language	English
Publishing date	2023-04-14
Publishing country	Canada
Document type	Journal Article ; Review ; Research Support, Non-U.S. Gov't
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1438-8871
ISSN (online)	1438-8871
ISSN	1438-8871
DOI	10.2196/45465
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Article ; Online: Excessive Smartphone Use and Self-Esteem Among Adults With Internet Gaming Disorder: Quantitative Survey Study.

Kim, Hyunmin / Choi, In Young / Kim, Dai-Jin

JMIR mHealth and uHealth

2020 Volume 8, Issue 9, Page(s) e18505

Abstract: Background: Smartphone overuse can harm individual health and well-being. Although several studies have explored the relationship between problematic or excessive smartphone use and mental health, much less is known about effects on self-esteem, which ... ...

Abstract	Background: Smartphone overuse can harm individual health and well-being. Although several studies have explored the relationship between problematic or excessive smartphone use and mental health, much less is known about effects on self-esteem, which is essential in having a healthy life, among adults with mental health disorders, including internet gaming disorder. Furthermore, given that smartphone usage differs by gender, little is known about gender differences in the relationship between smartphone overuse and self-esteem. Objective: The objective of this study was to assess self-esteem among individuals with mental health disorders and explore the relationship with excessive smartphone use. Methods: Participants were selected based on their responses to the internet gaming disorder assessment, which includes 9 items developed based on Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) criteria, from among a Korean cohort of smartphone users aged 20-40 years, resulting in a sample of 189 participants (men:120, women: 69). The Rosenberg self-esteem scale and the Korean smartphone addiction proneness scale were utilized to assess the outcome self-esteem with excessive smartphone use as the primary independent variable. Guided by the Bowlby attachment theory and prior studies, we selected several covariates. Generalized linear regression analyses, as well as subgroup analyses by gender, were performed. Results: Among adults with internet gaming disorder, the average Korean smartphone addiction proneness scale score was significantly higher in women than that in men (41.30 vs. 37.94; P=.001), and excessive smartphone use was significantly more prevalent in women than it was in men (30.43% vs. 20.83%; P=.02). Our findings from the generalized linear regression analyses indicated that an increase in Korean smartphone addiction proneness scale score had a negative relationship with self-esteem among those with internet gaming disorder (β=-0.18, P=.001). Furthermore, our interaction models showed that, among those with internet gaming disorder, more men than women had lower self-esteem associated with an increase in Korean smartphone addiction proneness scale score and a high degree of smartphone overuse (β=-0.19, P=.004; β=-3.73, P<.001). Conclusions: Excessive smartphone use was found to be adversely associated with self-esteem among young and middle-aged adults with internet gaming disorder; notably, more men than women were negatively influenced (regarding self-esteem) by smartphone overuse. Based on our findings, more efforts should be made to reduce excessive or problematic smartphone use by considering developing public health interventions or policy, particularly among those with mental health disorders such as internet gaming disorder.
MeSH term(s)	Adult ; Behavior, Addictive/epidemiology ; Female ; Humans ; Internet Addiction Disorder ; Male ; Smartphone ; Surveys and Questionnaires ; Video Games ; Young Adult
Language	English
Publishing date	2020-09-29
Publishing country	Canada
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2719220-9
ISSN	2291-5222 ; 2291-5222
ISSN (online)	2291-5222
ISSN	2291-5222
DOI	10.2196/18505
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