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1. HyperCLOVA X Technical Report

Author

Yoo, Kang Min, Han, Jaegeun, In, Sookyo, Jeon, Heewon, Jeong, Jisu, Kang, Jaewook, Kim, Hyunwook, Kim, Kyung-Min, Kim, Munhyong, Kim, Sungju, Kwak, Donghyun, Kwak, Hanock, Kwon, Se Jung, Lee, Bado, Lee, Dongsoo, Lee, Gichang, Lee, Jooho, Park, Baeseong, Shin, Seongjin, Yu, Joonsang, Baek, Seolki, Byeon, Sumin, Cho, Eungsup, Choe, Dooseok, Han, Jeesung, Jin, Youngkyun, Jun, Hyein, Jung, Jaeseung, Kim, Chanwoong, Kim, Jinhong, Kim, Jinuk, Lee, Dokyeong, Park, Dongwook, Sohn, Jeong Min, Han, Sujung, Heo, Jiae, Hong, Sungju, Jeon, Mina, Jung, Hyunhoon, Jung, Jungeun, Jung, Wangkyo, Kim, Chungjoon, Kim, Hyeri, Kim, Jonghyun, Kim, Min Young, Lee, Soeun, Park, Joonhee, Shin, Jieun, Yang, Sojin, Yoon, Jungsoon, Lee, Hwaran, Bae, Sanghwan, Cha, Jeehwan, Gylleus, Karl, Ham, Donghoon, Hong, Mihak, Hong, Youngki, Hong, Yunki, Jang, Dahyun, Jeon, Hyojun, Jeon, Yujin, Jeong, Yeji, Ji, Myunggeun, Jin, Yeguk, Jo, Chansong, Joo, Shinyoung, Jung, Seunghwan, Kim, Adrian Jungmyung, Kim, Byoung Hoon, Kim, Hyomin, Kim, Jungwhan, Kim, Minkyoung, Kim, Minseung, Kim, Sungdong, Kim, Yonghee, Kim, Youngjun, Kim, Youngkwan, Ko, Donghyeon, Lee, Dughyun, Lee, Ha Young, Lee, Jaehong, Lee, Jieun, Lee, Jonghyun, Lee, Jongjin, Lee, Min Young, Lee, Yehbin, Min, Taehong, Min, Yuri, Moon, Kiyoon, Oh, Hyangnam, Park, Jaesun, Park, Kyuyon, Park, Younghun, Seo, Hanbae, Seo, Seunghyun, Sim, Mihyun, Son, Gyubin, Yeo, Matt, Yeom, Kyung Hoon, Yoo, Wonjoon, You, Myungin, Ahn, Doheon, Ahn, Homin, Ahn, Joohee, Ahn, Seongmin, An, Chanwoo, An, Hyeryun, An, Junho, An, Sang-Min, Byun, Boram, Byun, Eunbin, Cha, Jongho, Chang, Minji, Chang, Seunggyu, Cho, Haesong, Cho, Youngdo, Choi, Dalnim, Choi, Daseul, Choi, Hyoseok, Choi, Minseong, Choi, Sangho, Choi, Seongjae, Choi, Wooyong, Chun, Sewhan, Go, Dong Young, Ham, Chiheon, Han, Danbi, Han, Jaemin, Hong, Moonyoung, Hong, Sung Bum, Hwang, Dong-Hyun, Hwang, Seongchan, Im, Jinbae, Jang, Hyuk Jin, Jang, Jaehyung, Jang, Jaeni, Jang, Sihyeon, Jang, Sungwon, Jeon, Joonha, Jeong, Daun, Jeong, Joonhyun, Jeong, Kyeongseok, Jeong, Mini, Jin, Sol, Jo, Hanbyeol, Jo, Hanju, Jo, Minjung, Jung, Chaeyoon, Jung, Hyungsik, Jung, Jaeuk, Jung, Ju Hwan, Jung, Kwangsun, Jung, Seungjae, Ka, Soonwon, Kang, Donghan, Kang, Soyoung, Kil, Taeho, Kim, Areum, Kim, Beomyoung, Kim, Byeongwook, Kim, Daehee, Kim, Dong-Gyun, Kim, Donggook, Kim, Donghyun, Kim, Euna, Kim, Eunchul, Kim, Geewook, Kim, Gyu Ri, Kim, Hanbyul, Kim, Heesu, Kim, Isaac, Kim, Jeonghoon, Kim, Jihye, Kim, Joonghoon, Kim, Minjae, Kim, Minsub, Kim, Pil Hwan, Kim, Sammy, Kim, Seokhun, Kim, Seonghyeon, Kim, Soojin, Kim, Soong, Kim, Soyoon, Kim, Sunyoung, Kim, Taeho, Kim, Wonho, Kim, Yoonsik, Kim, You Jin, Kim, Yuri, Kwon, Beomseok, Kwon, Ohsung, Kwon, Yoo-Hwan, Lee, Anna, Lee, Byungwook, Lee, Changho, Lee, Daun, Lee, Dongjae, Lee, Ha-Ram, Lee, Hodong, Lee, Hwiyeong, Lee, Hyunmi, Lee, Injae, Lee, Jaeung, Lee, Jeongsang, Lee, Jisoo, Lee, Jongsoo, Lee, Joongjae, Lee, Juhan, Lee, Jung Hyun, Lee, Junghoon, Lee, Junwoo, Lee, Se Yun, Lee, Sujin, Lee, Sungjae, Lee, Sungwoo, Lee, Wonjae, Lee, Zoo Hyun, Lim, Jong Kun, Lim, Kun, Lim, Taemin, Na, Nuri, Nam, Jeongyeon, Nam, Kyeong-Min, Noh, Yeonseog, Oh, Biro, Oh, Jung-Sik, Oh, Solgil, Oh, Yeontaek, Park, Boyoun, Park, Cheonbok, Park, Dongju, Park, Hyeonjin, Park, Hyun Tae, Park, Hyunjung, Park, Jihye, Park, Jooseok, Park, Junghwan, Park, Jungsoo, Park, Miru, Park, Sang Hee, Park, Seunghyun, Park, Soyoung, Park, Taerim, Park, Wonkyeong, Ryu, Hyunjoon, Ryu, Jeonghun, Ryu, Nahyeon, Seo, Soonshin, Seo, Suk Min, Shim, Yoonjeong, Shin, Kyuyong, Shin, Wonkwang, Sim, Hyun, Sim, Woongseob, Soh, Hyejin, Son, Bokyong, Son, Hyunjun, Son, Seulah, Song, Chi-Yun, Song, Chiyoung, Song, Ka Yeon, Song, Minchul, Song, Seungmin, Wang, Jisung, Yeo, Yonggoo, Yi, Myeong Yeon, Yim, Moon Bin, Yoo, Taehwan, Yoo, Youngjoon, Yoon, Sungmin, Yoon, Young Jin, Yu, Hangyeol, Yu, Ui Seon, Zuo, Xingdong, Bae, Jeongin, Bae, Joungeun, Cho, Hyunsoo, Cho, Seonghyun, Cho, Yongjin, Choi, Taekyoon, Choi, Yera, Chung, Jiwan, Han, Zhenghui, Heo, Byeongho, Hong, Euisuk, Hwang, Taebaek, Im, Seonyeol, Jegal, Sumin, Jeon, Sumin, Jeong, Yelim, Jeong, Yonghyun, Jiang, Can, Jiang, Juyong, Jin, Jiho, Jo, Ara, Jo, Younghyun, Jung, Hoyoun, Jung, Juyoung, Kang, Seunghyeong, Kim, Dae Hee, Kim, Ginam, Kim, Hangyeol, Kim, Heeseung, Kim, Hyojin, Kim, Hyojun, Kim, Hyun-Ah, Kim, Jeehye, Kim, Jin-Hwa, Kim, Jiseon, Kim, Jonghak, Kim, Jung Yoon, Kim, Rak Yeong, Kim, Seongjin, Kim, Seoyoon, Kim, Sewon, Kim, Sooyoung, Kim, Sukyoung, Kim, Taeyong, Ko, Naeun, Koo, Bonseung, Kwak, Heeyoung, Kwon, Haena, Kwon, Youngjin, Lee, Boram, Lee, Bruce W., Lee, Dagyeong, Lee, Erin, Lee, Euijin, Lee, Ha Gyeong, Lee, Hyojin, Lee, Hyunjeong, Lee, Jeeyoon, Lee, Jeonghyun, Lee, Jongheok, Lee, Joonhyung, Lee, Junhyuk, Lee, Mingu, Lee, Nayeon, Lee, Sangkyu, Lee, Se Young, Lee, Seulgi, Lee, Seung Jin, Lee, Suhyeon, Lee, Yeonjae, Lee, Yesol, Lee, Youngbeom, Lee, Yujin, Li, Shaodong, Liu, Tianyu, Moon, Seong-Eun, Moon, Taehong, Nihlenramstroem, Max-Lasse, Oh, Wonseok, Oh, Yuri, Park, Hongbeen, Park, Hyekyung, Park, Jaeho, Park, Nohil, Park, Sangjin, Ryu, Jiwon, Ryu, Miru, Ryu, Simo, Seo, Ahreum, Seo, Hee, Seo, Kangdeok, Shin, Jamin, Shin, Seungyoun, Sin, Heetae, Wang, Jiangping, Wang, Lei, Xiang, Ning, Xiao, Longxiang, Xu, Jing, Yi, Seonyeong, Yoo, Haanju, Yoo, Haneul, Yoo, Hwanhee, Yu, Liang, Yu, Youngjae, Yuan, Weijie, Zeng, Bo, Zhou, Qian, Cho, Kyunghyun, Ha, Jung-Woo, Park, Joonsuk, Hwang, Jihyun, Kwon, Hyoung Jo, Kwon, Soonyong, Lee, Jungyeon, Lee, Seungho, Lim, Seonghyeon, Noh, Hyunkyung, Choi, Seungho, Lee, Sang-Woo, Lim, Jung Hwa, and Sung, Nako

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. HyperCLOVA X was trained on a balanced mix of Korean, English, and code data, followed by instruction-tuning with high-quality human-annotated datasets while abiding by strict safety guidelines reflecting our commitment to responsible AI. The model is evaluated across various benchmarks, including comprehensive reasoning, knowledge, commonsense, factuality, coding, math, chatting, instruction-following, and harmlessness, in both Korean and English. HyperCLOVA X exhibits strong reasoning capabilities in Korean backed by a deep understanding of the language and cultural nuances. Further analysis of the inherent bilingual nature and its extension to multilingualism highlights the model's cross-lingual proficiency and strong generalization ability to untargeted languages, including machine translation between several language pairs and cross-lingual inference tasks. We believe that HyperCLOVA X can provide helpful guidance for regions or countries in developing their sovereign LLMs., Comment: 44 pages; updated authors list and fixed author names

Published
2024

2. Rare Case of Echinostoma cinetorchis Infection, South Korea

Author

Hong, Sooji, Shin, Hyejoo, Lee, Yoon-Hee, Hong, Sung-Jong, Kim, So-Ri, Kim, Youn-Kyoung, Son, Young-Jin, Song, Jeong- Gil, Chai, Jong-Yil, and Jung, Bong-Kwang

Subjects
Fluke infections -- Case studies -- Causes of, Gastrointestinal diseases -- Case studies -- Causes of
Abstract

Echinostomes are zoonotic intestinal flukes infecting birds and mammals worldwide (1,2). Adult echinostomes generally inhabit the small intestines of the definitive host and attach to the mucosal surface, causing pathological [...]

Published
2024

3. Association of Cough Severity with Asthma Control and Quality of Life in Patients with Severe Asthma

Author

Lee, Hwa Young, Lee, Youngsoo, Lee, Ji-Hyang, Lee, Seung-Eun, Sim, Da Woon, Kang, Noeul, Kim, Joo-Hee, Kang, Sung-Yoon, Sohn, Kyoung-Hee, Nam, Young Hee, Kim, Sujeong, Park, Chan Sun, Kim, So Ri, An, Jin, Kim, Byung-Keun, Jin, Hyun Jung, Park, So-Young, Lee, Byung-Jae, Lee, Sook Young, Park, Hae-Sim, Cho, You Sook, Kim, Sang-Heon, and Song, Woo-Jung

Published
2024
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13. Personality Disorders

Author

Widiger, Thomas A., Tyrer, Peter, McCabe, Gillian A., Kim, Youl-Ri, Ng, Chee H., Section editor, Lecic-Tosevski, Dusica, Section editor, Alfonso, César A., Section editor, Salloum, Ihsan M., Section editor, Tasman, Allan, editor, Riba, Michelle B., editor, Alarcón, Renato D., editor, Alfonso, César A., editor, Kanba, Shigenobu, editor, Lecic-Tosevski, Dusica, editor, Ndetei, David M., editor, Ng, Chee H., editor, and Schulze, Thomas G., editor

Published
2024
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18. Using Markedness Principle for Abstraction of Dependency Relations of Natural Languages

Author

Kim, Ju-Ri

Abstract

Background/Objectives: There is no attempt to investigate the relationships between dependency and markedness even though the syntactic roles in language are decided by dependency relations and markers. The main objective of this study was to understand markedness beyond syntactical tables and propose a syntax graph with various syntax structures to verify the relationship between dependence of proposed markers. Methods/Statistical analysis: The methodology involved enquiry into the origin and development of dependency relations, starting from their definition, abstraction, and usage in syntactic structures through graphical presentations. Findings: This study revealed that dependency relations denoted by the markers can be classified into two types of dependencies according to their syntactic functions: implicit and explicit. Eventually, this markedness can be presented through syntax graphs of various syntactic structures to validate the functions of the markers and dependency relations. Improvements/Applications: This paper presents a reasonable method to define dependency relations based on the markedness and the valence theory of the predicate. This approach provides a systematic view to define dependency relations for natural language processing. The implementation of syntax graphs is a future research project.

Published
2021

27. Similarities and Differences of Interventions to Promote Physical and Psychological Health Between Prefrail and Frail Older Women: A Systematic Review

Author

Jeong, Ha Na, Chang, Sun Ju, Kim, Joo Ri, and Choi, Gi Won

Subjects
Women -- Health aspects, Frail elderly -- Demographic aspects -- Care and treatment, Mental health -- Care and treatment, Health, Seniors
Abstract

The current review aimed to explore similarities and differences in the properties of interventions that promote physical and psychological health between prefrail and frail older women. Ten databases were searched for studies published from database inception to May 2023. Two Cochrane tools were used to assess the risk of bias in experimental and quasi-experimental studies. Twenty-three studies were selected, including 11 studies on prefrailty and 12 studies on frailty. Exercise interventions were predominant, but the contents and standards of exercise intensity were inconsistent between prefrail and frail women. For the main outcomes of the interventions, balance ability and biochemical factors were measured more frequently for frail older women than prefrail older women. Psychological health was less measured for prefrail and frail older women compared to physical health. Future research needs to consider balance training, as well as the evaluation of biochemical factors and psychological health among prefrail or frail older women. [Journal of Gerontological Nursing, 49(10), 20–28.], Frailty is an age-associated condition characterized by the accumulation of physical, psychological, and social deficiencies (Sacha et al., 2017). According to its severity, frailty is classified as prefrailty and frailty. [...]

Published
2023
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31. Impact of COVID-19 Lockdown in Eating Disorders: A Multicentre Collaborative International Study

Author

Baenas, Isabel, Etxandi, Mikel, Munguía, Lucero, Granero, Roser, Mestre-Bach, Gemma, Sánchez, Isabel, Ortega, Emilio, Andreu, Alba, Moize, Violeta L, Fernández-Real, Jose-Manuel, Tinahones, Francisco J, Diéguez, Carlos, Frühbeck, Gema, Le Grange, Daniel, Tchanturia, Kate, Karwautz, Andreas, Zeiler, Michael, Imgart, Hartmut, Zanko, Annika, Favaro, Angela, Claes, Laurence, Shekriladze, Ia, Serrano-Troncoso, Eduardo, Cecilia-Costa, Raquel, Rangil, Teresa, Loran-Meler, Maria Eulalia, Soriano-Pacheco, José, Carceller-Sindreu, Mar, Navarrete, Rosa, Lozano, Meritxell, Linares, Raquel, Gudiol, Carlota, Carratala, Jordi, Plana, Maria T, Graell, Montserrat, González-Parra, David, Barrio, José A Gómez-del, Sepúlveda, Ana R, Sánchez-González, Jéssica, Machado, Paulo PP, Håkansson, Anders, Túry, Ferenc, Pászthy, Bea, Stein, Daniel, Papezová, Hana, Gricova, Jana, Bax, Brigita, Borisenkov, Mikhail F, Popov, Sergey V, Gubin, Denis G, Petrov, Ivan M, Isakova, Dilara, Mustafina, Svetlana V, Kim, Youl-Ri, Nakazato, Michiko, Godart, Nathalie, van Voren, Robert, Ilnytska, Tetiana, Chen, Jue, Rowlands, Katie, Voderholzer, Ulrich, Monteleone, Alessio M, Treasure, Janet, Jiménez-Murcia, Susana, and Fernández-Aranda, Fernando

Subjects
Eating Disorders, Health Services, Behavioral and Social Science, Nutrition, Clinical Research, Mental Health, Prevention, Brain Disorders, Mental health, Good Health and Well Being, Adolescent, Adult, Asia, COVID-19, Child, Europe, Feeding and Eating Disorders, Female, Humans, Internationality, Longitudinal Studies, Male, Quarantine, SARS-CoV-2, Social Isolation, Young Adult, eating disorders, COVID-19 lockdown, COVID-19 Isolation Eating Scale, eating symptoms, psychological impact, Food Sciences, Nutrition and Dietetics
Abstract

The COVID-19 lockdown has had a significant impact on mental health. Patients with eating disorders (ED) have been particularly vulnerable. (1) To explore changes in eating-related symptoms and general psychopathology during lockdown in patients with an ED from various European and Asian countries; and (2) to assess differences related to diagnostic ED subtypes, age, and geography. The sample comprised 829 participants, diagnosed with an ED according to DSM-5 criteria from specialized ED units in Europe and Asia. Participants were assessed using the COVID-19 Isolation Scale (CIES). Patients with binge eating disorder (BED) experienced the highest impact on weight and ED symptoms in comparison with other ED subtypes during lockdown, whereas individuals with other specified feeding and eating disorders (OFSED) had greater deterioration in general psychological functioning than subjects with other ED subtypes. Finally, Asian and younger individuals appeared to be more resilient. The psychopathological changes in ED patients during the COVID-19 lockdown varied by cultural context and individual variation in age and ED diagnosis. Clinical services may need to target preventive measures and adapt therapeutic approaches for the most vulnerable patients.

Published
2022

40. Feasibility of two-dimensional die-level plasma process monitoring using spatially resolvable optical emission spectrometers

Author

Lee, Jin Young, Kim, Dae-Woong, Hur, Min, Song, Young-Hoon, Yi, Hun-Jung, Lee, Chang-Sug, Kim, Nu-Ri, and Kang, Woo Seok

Subjects
Spectrometer -- Usage, Physics
Abstract

We demonstrated the feasibility of die-level process monitoring using spatially resolvable optical emission spectrometers (SROESs) in a low-pressure plasma reactor. The spatially resolved Ar emission line intensities and their intensity ratios were obtained from uniformly generated and intentionally perturbed plasma by inserting conductors of known sizes at known locations. The sheath and perturbed plasma distributions were identified from the Ar emission line intensity and their intensity ratio in the lateral direction to the SROES installment orientation. However, the resolution in the axial direction was insufficient to identify the sheath and perturbed the plasma distribution. We propose the superimposition of measured plasma emission intensities from two perpendicularly aligned SROESs for die-level process monitoring. The insufficient axial resolution can be compensated for by the lateral resolution of another SROES, and die-level process monitoring using SROES can thus be realized. Key words: spatially resolved optical emission spectroscopy, die-level process monitoring, abnormal event monitoring, superimposing method, process uniformity, 1. Introduction As semiconductor or OLED/LCD display manufacturing requires harsh processes, process monitoring technologies with optimized sensors in plasma processes are becoming increasingly important, such as ashing, reactive ion etching, [...]

Published
2023
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44. Population health outcomes in South Korea 1990–2019, and projections up to 2040: a systematic analysis for the Global Burden of Disease Study 2019

Author

Park, Seoyeon, Kim, Min Seo, Yon, Dong Keon, Lee, Seung Won, Ward, Joseph L, McLaughlin, Susan A, Mehlman, Max L, Koyanagi, Ai, Smith, Lee, Jacob, Louis, Agampodi, Suneth Buddhika, Beiranvand, Maryam, Choi, Dong-Woo, Hong, Sung Hwi, Hosseinzadeh, Mehdi, Kim, Cho-il, Kim, Gyu Ri, Kim, Jihee, Kim, Kwanghyun, Kim, Sungroul, Lee, Doo Woong, Lee, Hankil, Lee, Sang-woong, Lee, Yo Han, Mokdad, Ali H, Murray, Christopher J L, Okekunle, Akinkunmi Paul, Park, Eun-Cheol, Rabiee, Navid, Shin, Youn Ho, Hay, Simon I, and Shin, Jae Il

Published
2023
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47. Shared genetic risk between eating disorder‐ and substance‐use‐related phenotypes: Evidence from genome‐wide association studies

Author

Munn‐Chernoff, Melissa A, Johnson, Emma C, Chou, Yi‐Ling, Coleman, Jonathan RI, Thornton, Laura M, Walters, Raymond K, Yilmaz, Zeynep, Baker, Jessica H, Hübel, Christopher, Gordon, Scott, Medland, Sarah E, Watson, Hunna J, Gaspar, Héléna A, Bryois, Julien, Hinney, Anke, Leppä, Virpi M, Mattheisen, Manuel, Ripke, Stephan, Yao, Shuyang, Giusti‐Rodríguez, Paola, Hanscombe, Ken B, Adan, Roger AH, Alfredsson, Lars, Ando, Tetsuya, Andreassen, Ole A, Berrettini, Wade H, Boehm, Ilka, Boni, Claudette, Perica, Vesna Boraska, Buehren, Katharina, Burghardt, Roland, Cassina, Matteo, Cichon, Sven, Clementi, Maurizio, Cone, Roger D, Courtet, Philippe, Crow, Scott, Crowley, James J, Danner, Unna N, Davis, Oliver SP, de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece E, Dick, Danielle M, Dikeos, Dimitris, Dina, Christian, Dmitrzak‐Weglarz, Monika, Docampo, Elisa, Duncan, Laramie E, Egberts, Karin, Ehrlich, Stefan, Escaramís, Geòrgia, Esko, Tõnu, Estivill, Xavier, Farmer, Anne, Favaro, Angela, Fernández‐Aranda, Fernando, Fichter, Manfred M, Fischer, Krista, Föcker, Manuel, Foretova, Lenka, Forstner, Andreas J, Forzan, Monica, Franklin, Christopher S, Gallinger, Steven, Giegling, Ina, Giuranna, Johanna, Gonidakis, Fragiskos, Gorwood, Philip, Mayora, Monica Gratacos, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Hatzikotoulas, Konstantinos, Hauser, Joanna, Hebebrand, Johannes, Helder, Sietske G, Herms, Stefan, Herpertz‐Dahlmann, Beate, Herzog, Wolfgang, Huckins, Laura M, Hudson, James I, Imgart, Hartmut, Inoko, Hidetoshi, Janout, Vladimir, Jiménez‐Murcia, Susana, Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Karhunen, Leila, Karwautz, Andreas, Kas, Martien JH, Kennedy, James L, Keski‐Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl‐Ri, Klump, Kelly L, Knudsen, Gun Peggy S, and La Via, Maria C

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Epidemiology, Health Sciences, Psychology, Pharmacology and Pharmaceutical Sciences, Nutrition, Brain Disorders, Alcoholism, Alcohol Use and Health, Mental Health, Eating Disorders, Substance Misuse, Genetics, Tobacco Smoke and Health, Tobacco, Human Genome, Drug Abuse (NIDA only), Prevention, Clinical Research, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Good Health and Well Being, Alcoholism, Depressive Disorder, Major, Feeding and Eating Disorders, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Schizophrenia, Substance-Related Disorders, Tobacco Use Disorder, eating disorders, genetic correlation, substance use, Medical and Health Sciences, Psychology and Cognitive Sciences, Substance Abuse, Biomedical and clinical sciences, Health sciences
Abstract

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.

Published
2021

49. The impact of spatial clustering on the labour productivity of the UK tourism and hospitality industry

Author

Kim, Yoo Ri, Williams, Allan, Chen, Jason, and Park, Sangwon

Subjects
647.94068
Abstract

This research aims to investigate the impact of spatial clustering of T&H firms on the labour productivity of the UK T&H industry, specifically on the implications of agglomeration economies for labour productivity both within (direct effects, accounting for spatial feedback effects) and between (indirect spatial spillover effects) spatial units. Employing under-exploited micro-level datasets from the UK Office for National Statistics, the impact of spatial clustering and agglomeration economies (labour market pooling and knowledge spillovers) on T&H labour productivity within and between local authority districts (LADs) was examined using spatial panel modelling. Based on 373 LADs across England, Scotland and Wales and for the period 2006-2016, the fixed-effect spatial Durbin panel model was estimated. Findings concluded that the increase in the degree of clustering of T&H firms has had negative effects on labour productivity of T&H firms within the LADs but also across, and from, neighbouring LADs and back. Labour market pooling variables have shown positive effects regarding the pool of skilled labour but the effects on productivity were negative in terms of the share in high-skilled jobs. Knowledge spillover effects on labour productivity of T&H firms within a LAD were insignificant, but when considering its spatial spillover effects, they were complementary, suggesting the importance of human capital externalities and their spillover effects across geographical boundaries. Moreover, the long-run effects of agglomeration economies were significantly greater than the short-run effects on the labour productivity of T&H firms within and between LADs, suggesting the need to take a long-run perspective on how spatial clustering and agglomeration economies affect T&H labour productivity within and between neighbouring regions. Using geographically weighted regression modelling, significant spatial variations in the relationship between spatial clustering and agglomeration economies and T&H labour productivity were identified within each LAD but also spillover effects across the neighbouring districts.

Published
2020
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50. COVID Isolation Eating Scale (CIES): Analysis of the impact of confinement in eating disorders and obesity—A collaborative international study

Author

Fernández‐Aranda, Fernando, Munguía, Lucero, Mestre‐Bach, Gemma, Steward, Trevor, Etxandi, Mikel, Baenas, Isabel, Granero, Roser, Sánchez, Isabel, Ortega, Emilio, Andreu, Alba, Moize, Violeta L, Fernández‐Real, Jose M, Tinahones, Francisco J, Diegüez, Carlos, Frühbeck, Gema, Le Grange, Daniel, Tchanturia, Kate, Karwautz, Andreas, Zeiler, Michael, Favaro, Angela, Claes, Laurence, Luyckx, Koen, Shekriladze, Ia, Serrano‐Troncoso, Eduardo, Rangil, Teresa, Meler, Maria Eulalia Loran, Soriano‐Pacheco, Jose, Carceller‐Sindreu, Mar, Bujalance‐Arguijo, Sara, Lozano, Meritxell, Linares, Raquel, Gudiol, Carlota, Carratala, Jordi, Sanchez‐Gonzalez, Jessica, Machado, Paulo PP, Håkansson, Anders, Túry, Ferenc, Pászthy, Bea, Stein, Daniel, Papezová, Hana, Bax, Brigita, Borisenkov, Mikhail F, Popov, Sergey V, Kim, Youl‐Ri, Nakazato, Michiko, Godart, Nathalie, Voren, Robert, Ilnytska, Tetiana, Chen, Jue, Rowlands, Katie, Treasure, Janet, and Jiménez‐Murcia, Susana

Subjects
Clinical Research, Anorexia, Behavioral and Social Science, Eating Disorders, Nutrition, Brain Disorders, Mental Health, Mental health, Good Health and Well Being, Adolescent, Adult, Aged, COVID-19, Factor Analysis, Statistical, Feeding and Eating Disorders, Female, Humans, Male, Middle Aged, Obesity, Psychiatric Status Rating Scales, Psychometrics, Social Isolation, Spain, Young Adult, COVID Isolation Eating Scale, eating disorders, obesity, Clinical Sciences, Psychology, Clinical Psychology
Abstract

Confinement during the COVID-19 pandemic is expected to have a serious and complex impact on the mental health of patients with an eating disorder (ED) and of patients with obesity. The present manuscript has the following aims: (1) to analyse the psychometric properties of the COVID Isolation Eating Scale (CIES), (2) to explore changes that occurred due to confinement in eating symptomatology; and (3) to explore the general acceptation of the use of telemedicine during confinement. The sample comprised 121 participants (87 ED patients and 34 patients with obesity) recruited from six different centres. Confirmatory Factor Analyses (CFA) tested the rational-theoretical structure of the CIES. Adequate goodness-of-fit was obtained for the confirmatory factor analysis, and Cronbach alpha values ranged from good to excellent. Regarding the effects of confinement, positive and negative impacts of the confinement depends of the eating disorder subtype. Patients with anorexia nervosa (AN) and with obesity endorsed a positive response to treatment during confinement, no significant changes were found in bulimia nervosa (BN) patients, whereas Other Specified Feeding or Eating Disorder (OSFED) patients endorsed an increase in eating symptomatology and in psychopathology. Furthermore, AN patients expressed the greatest dissatisfaction and accommodation difficulty with remote therapy when compared with the previously provided face-to-face therapy. The present study provides empirical evidence on the psychometric robustness of the CIES tool and shows that a negative confinement impact was associated with ED subtype, whereas OSFED patients showed the highest impairment in eating symptomatology and in psychopathology.

Published
2020

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