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1. Exposure and connectedness to natural environments: An examination of the measurement invariance of the Nature Exposure Scale (NES) and Connectedness to Nature Scale (CNS) across 65 nations, 40 languages, gender identities, and age groups

Author

Swami, Viren, White, Mathew P., Voracek, Martin, Tran, Ulrich S., Aavik, Toivo, Ranjbar, Hamed Abdollahpour, Adebayo, Sulaiman Olanrewaju, Afhami, Reza, Ahmed, Oli, Aimé, Annie, Akel, Marwan, Al Halbusi, Hussam, Alexias, George, Ali, Khawla F., Alp-Dal, Nursel, Alsalhani, Anas B., Álvarez-Solas, Sara, Soares Amaral, Ana Carolina, Andrianto, Sonny, Aspden, Trefor, Argyrides, Marios, Aruta, John Jamir Benzon R., Atkin, Stephen, Ayandele, Olusola, Baceviciene, Migle, Bahbouh, Radvan, Ballesio, Andrea, Barron, David, Bellard, Ashleigh, Bender, SóleySesselja, Beydaǧ, Kerime Derya, Birovljević, Gorana, Blackburn, Marie-Ève, Borja-Alvarez, Teresita, Borowiec, Joanna, Bozogáňová, Miroslava, Bratland-Sanda, Solfrid, Browning, MatthewH.E.M., Brytek-Matera, Anna, Burakova, Marina, Çakır-Koçak, Yeliz, Camacho, Pablo, Camilleri, Vittorio Emanuele, Cazzato, Valentina, Cerea, Silvia, Chaiwutikornwanich, Apitchaya, Chaleeraktrakoon, Trawin, Chambers, Tim, Chen, Qing-Wei, Chen, Xin, Chien, Chin-Lung, Chobthamkit, Phatthanakit, Choompunuch, Bovornpot, Compte, Emilio J., Corrigan, Jennifer, Cosmas, Getrude, Cowden, Richard G., Czepczor-Bernat, Kamila, Czub, Marcin, Roberto da Silva, Wanderson, Dadfar, Mahboubeh, Dalley, Simon E., Dany, Lionel, Datu, Jesus Alfonso D., Berbert de Carvalho, Pedro Henrique, Lins de Holanda Coelho, Gabriel, De Jesus, Avila Odia S., Debbabi, Sonia Harzallah, Dhakal, Sandesh, Di Bernardo, Francesca, Dimitrova, Donka D., Dion, Jacinthe, Dixson, Barnaby, Donofrio, Stacey M., Drysch, Marius, Du, Hongfei, Dzhambov, Angel M., El-Jor, Claire, Enea, Violeta, Eskin, Mehmet, Farbod, Farinaz, Farrugia, Lorleen, Fian, Leonie, Fisher, Maryanne L., Folwarczny, Michał, Frederick, David A., Fuller-Tyszkiewicz, Matthew, Furnham, Adrian, García, Antonio Alías, Geller, Shulamit, Ghisi, Marta, Ghorbani, Alireza, Gomez Martinez, Maria Angeles, Gradidge, Sarah, Graf, Sylvie, Grano, Caterina, Gyene, Gyöngyvér, Hallit, Souheil, Hamdan, Motasem, Handelzalts, Jonathan E., Hanel, PaulH.P., Hawks, Steven R., Hekmati, Issa, Helmy, Mai, Hill, Tetiana, Hina, Farah, Holenweger, Geraldine, Hřebíčková, Martina, Ijabadeniyi, Olasupo Augustine, Imam, Asma, İnce, Başak, Irrazabal, Natalia, Jankauskiene, Rasa, Jiang, Ding-Yu, Jiménez-Borja, Micaela, Jiménez-Borja, Verónica, Johnson, Evan M., Jovanović, Veljko, Jović, Marija, Jović, Marko, Pereira Junqueira, Alessandra Costa, Kahle, Lisa-Marie, Kantanista, Adam, Karakiraz, Ahmet, Karkin, Ayşe Nur, Kasten, Erich, Khatib, Salam, Khieowan, Nuannut, Kimong, Patricia Joseph, Kiropoulos, Litza, Knittel, Joshua, Kohli, Neena, Koprivnik, Mirjam, Kospakov, Aituar, Król-Zielińska, Magdalena, Krug, Isabel, Kuan, Garry, Kueh, Yee Cheng, Kujan, Omar, Kukić, Miljana, Kumar, Sanjay, Kumar, Vipul, Lamba, Nishtha, Lauri, Mary Anne, Laus, Maria Fernanda, LeBlanc, Liza April, Lee, Hyejoo J., Lipowska, Małgorzata, Lipowski, Mariusz, Lombardo, Caterina, Lukács, Andrea, Maïano, Christophe, Malik, Sadia, Manjary, Mandar, Baldó, Lidia Márquez, Martinez-Banfi, Martha, Massar, Karlijn, Matera, Camilla, McAnirlin, Olivia, Mebarak, Moisés Roberto, Mechri, Anwar, Filgueiras Meireles, Juliana Fernandes, Mesko, Norbert, Mills, Jacqueline, Miyairi, Maya, Modi, Ritu, Modrzejewska, Adriana, Modrzejewska, Justyna, Mulgrew, Kate E., Myers, Taryn A., Namatame, Hikari, Nassani, Mohammad Zakaria, Nerini, Amanda, Neto, Félix, Neto, Joana, Neves, Angela Nogueira, Ng, Siu-Kuen, Nithiya, Devi, O, Jiaqing, Obeid, Sahar, Oda-Montecinos, Camila, Olapegba, Peter Olamakinde, Olonisakin, Tosin Tunrayo, Omar, Salma Samir, Örlygsdóttir, Brynja, Özsoy, Emrah, Otterbring, Tobias, Pahl, Sabine, Panasiti, Maria Serena, Park, Yonguk, Patwary, Muhammad Mainuddin, Pethö, Tatiana, Petrova, Nadezhda, Pietschnig, Jakob, Pourmahmoud, Sadaf, Prabhu, Vishnunarayan Girishan, Poštuvan, Vita, Prokop, Pavol, Ramseyer Winter, Virginia L., Razmus, Magdalena, Ru, Taotao, Rupar, Mirjana, Sahlan, Reza N., Hassan, Mohammad Salah, Šalov, Anđela, Sapkota, Saphal, Sarfo, Jacob Owusu, Sawamiya, Yoko, Schaefer, Katrin, Schulte-Mecklenbeck, Michael, Seekis, Veya, Selvi, Kerim, Sharifi, Mehdi, Shrivastava, Anita, Siddique, Rumana Ferdousi, Sigurdsson, Valdimar, Silkane, Vineta, Šimunić, Ana, Singh, Govind, Slezáčková, Alena, Sundgot-Borgen, Christine, Hoor, Gill Ten, Tevichapong, Passagorn, Tipandjan, Arun, Todd, Jennifer, Togas, Constantinos, Tonini, Fernando, Tovar-Castro, Juan Camilo, Jepsen Trangsrud, Lise Katrine, Tripathi, Pankaj, Tudorel, Otilia, Tylka, Tracy L., Uyzbayeva, Anar, Vally, Zahir, Vanags, Edmunds, Vega, Luis Diego, Vicente-Arruebarrena, Aitor, Vidal-Mollón, Jose, Vilar, Roosevelt, Villegas, Hyxia, Vintilă, Mona, Wallner, Christoph, Whitebridge, Simon, Windhager, Sonja, Wong, Kah Yan, Yau, Eric Kenson, Yamamiya, Yuko, Lan Yeung, Victoria Wai, Zanetti, Marcelo Callegari, Zawisza, Magdalena, Zeeni, Nadine, Zvaríková, Martina, and Stieger, Stefan

Published
2024
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3. An Analysis of the Longitudinal Changes in the Determining Factors for Adolescents’ Self-esteem with Random Forests

Author

Lee, Hyejoo, Jung, Euihyun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Park, Ji Su, editor, Yang, Laurence T., editor, Pan, Yi, editor, and Park, Jong Hyuk, editor

Published
2023
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5. Body appreciation around the world: Measurement invariance of the Body Appreciation Scale-2 (BAS-2) across 65 nations, 40 languages, gender identities, and age

Author

Swami, Viren, Tran, Ulrich S., Stieger, Stefan, Aavik, Toivo, Ranjbar, Hamed Abdollahpour, Adebayo, Sulaiman Olanrewaju, Afhami, Reza, Ahmed, Oli, Aimé, Annie, Akel, Marwan, Halbusi, Hussam Al, Alexias, George, Ali, Khawla F., Alp-Dal, Nursel, Alsalhani, Anas B., Álvares-Solas, Sara, Amaral, Ana Carolina Soares, Andrianto, Sonny, Aspden, Trefor, Argyrides, Marios, Aruta, John Jamir Benzon R., Atkin, Stephen, Ayandele, Olusola, Baceviciene, Migle, Bahbouh, Radvan, Ballesio, Andrea, Barron, David, Bellard, Ashleigh, Bender, Sóley Sesselja, Beydağ, Kerime Derya, Birovljević, Gorana, Blackburn, Marie-Ève, Borja-Alvarez, Teresita, Borowiec, Joanna, Bozogáňová, Miroslava, Bratland-Sanda, Solfrid, Browning, Matthew H.E.M., Brytek-Matera, Anna, Burakova, Marina, Çakır-Koçak, Yeliz, Camacho, Pablo, Camilleri, Vittorio Emanuele, Cazzato, Valentina, Cerea, Silvia, Chaiwutikornwanich, Apitchaya, Chaleeraktrakoon, Trawin, Chambers, Tim, Chen, Qing-Wei, Chen, Xin, Chien, Chin-Lung, Chobthamkit, Phatthanakit, Choompunuch, Bovornpot, Compte, Emilio J., Corrigan, Jennifer, Cosmas, Getrude, Cowden, Richard G., Czepczor-Bernat, Kamila, Czub, Marcin, da Silva, Wanderson Roberto, Dadfar, Mahboubeh, Dalley, Simon E., Dany, Lionel, Datu, Jesus Alfonso D., Berbert de Carvalho, Pedro Henrique, Coelho, Gabriel Lins de Holanda, De Jesus, Avila Odia S., Debbabi, Sonia Harzallah, Dhakal, Sandesh, Di Bernardo, Francesca, Dimitrova, Donka D., Dion, Jacinthe, Dixson, Barnaby, Donofrio, Stacey M., Drysch, Marius, Du, Hongfei, Dzhambov, Angel M., El-Jor, Claire, Enea, Violeta, Eskin, Mehmet, Farbod, Farinaz, Farrugia, Lorleen, Fian, Leonie, Fisher, Maryanne L., Folwarczny, Michał, Frederick, David A., Fuller-Tyszkiewicz, Matthew, Furnham, Adrian, García, Antonio Alías, Geller, Shulamit, Ghisi, Marta, Ghorbani, Alireza, Martinez, Maria Angeles Gomez, Gradidge, Sarah, Graf, Sylvie, Grano, Caterina, Gyene, Gyöngyvér, Hallit, Souheil, Hamdan, Motasem, Handelzalts, Jonathan E., Hanel, Paul H.P., Hawks, Steven R., Hekmati, Issa, Helmy, Mai, Hill, Tetiana, Hina, Farah, Holenweger, Geraldine, Hřebíčková, Martina, Ijabadeniyi, Olasupo Augustine, Imam, Asma, İnce, Başak, Irrazabal, Natalia, Jankauskiene, Rasa, Jiang, Ding-Yu, Jiménez-Borja, Micaela, Jiménez-Borja, Verónica, Johnson, Evan M., Jovanović, Veljko, Jović, Marija, Jović, Marko, Junqueira, Alessandra Costa Pereira, Kahle, Lisa-Marie, Kantanista, Adam, Karakiraz, Ahmet, Karkin, Ayşe Nur, Kasten, Erich, Khatib, Salam, Khieowan, Nuannut, Kimong, Patricia Joseph, Kiropoulos, Litza, Knittel, Joshua, Kohli, Neena, Koprivnik, Mirjam, Kospakov, Aituar, Król-Zielińska, Magdalena, Krug, Isabel, Kuan, Garry, Kueh, Yee Cheng, Kujan, Omar, Kukić, Miljana, Kumar, Sanjay, Kumar, Vipul, Lamba, Nishtha, Lauri, Mary Anne, Laus, Maria Fernanda, LeBlanc, Liza April, Lee, Hyejoo J., Lipowska, Małgorzata, Lipowski, Mariusz, Lombardo, Caterina, Lukács, Andrea, Maïano, Christophe, Malik, Sadia, Manjary, Mandar, Baldó, Lidia Márquez, Martinez-Banfi, Martha, Massar, Karlijn, Matera, Camilla, McAnirlin, Olivia, Mebarak, Moisés Roberto, Mechri, Anwar, Meireles, Juliana Fernandes Filgueiras, Mesko, Norbert, Mills, Jacqueline, Miyairi, Maya, Modi, Ritu, Modrzejewska, Adriana, Modrzejewska, Justyna, Mulgrew, Kate E., Myers, Taryn A., Namatame, Hikari, Nassani, Mohammad Zakaria, Nerini, Amanda, Neto, Félix, Neto, Joana, Neves, Angela Noguiera, Ng, Siu-Kuen, Nithiya, Devi, O, Jiaqing, Obeid, Sahar, Oda-Montecinos, Camila, Olapegba, Peter Olamakinde, Olonisakin, Tosin Tunrayo, Omar, Salma Samir, Örlygsdóttir, Brynja, Özsoy, Emrah, Otterbring, Tobias, Pahl, Sabine, Panasiti, Maria Serena, Park, Yonguk, Patwary, Muhammad Mainuddin, Pethö, Tatiana, Petrova, Nadezhda, Pietschnig, Jakob, Pourmahmoud, Sadaf, Prabhu, Vishnunarayan Girishan, Poštuvan, Vita, Prokop, Pavol, Ramseyer Winter, Virginia L., Razmus, Magdalena, Ru, Taotao, Rupar, Mirjana, Sahlan, Reza N., Hassan, Mohammad Salah, Šalov, Anđela, Sapkota, Saphal, Sarfo, Jacob Owusu, Sawamiya, Yoko, Schaefer, Katrin, Schulte-Mecklenbeck, Michael, Seekis, Veya, Selvi, Kerim, Sharifi, Mehdi, Shrivastava, Anita, Siddique, Rumana Ferdousi, Sigurdsson, Valdimar, Silkane, Vineta, Šimunić, Ana, Singh, Govind, Slezáčková, Alena, Sundgot-Borgen, Christine, Ten Hoor, Gill, Tevichapong, Passagorn, Tipandjan, Arun, Todd, Jennifer, Togas, Constantinos, Tonini, Fernando, Tovar-Castro, Juan Camilo, Trangsrud, Lise Katrine Jepsen, Tripathi, Pankaj, Tudorel, Otilia, Tylka, Tracy L., Uyzbayeva, Anar, Vally, Zahir, Vanags, Edmunds, Vega, Luis Diego, Vicente-Arruebarrena, Aitor, Vidal-Mollón, Jose, Vilar, Roosevelt, Villegas, Hyxia, Vintilă, Mona, Wallner, Christoph, White, Mathew P., Whitebridge, Simon, Windhager, Sonja, Wong, Kah Yan, Yau, Eric Kenson, Yamamiya, Yuko, Yeung, Victoria Wai Lan, Zanetti, Marcelo Callegari, Zawisza, Magdalena, Zeeni, Nadine, Zvaríková, Martina, and Voracek, Martin

Published
2023
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6. Association between APOE ε2 and Aβ burden in patients with Alzheimer- and vascular-type cognitive impairment.

Author

Lee, Jin San, Lee, Hyejoo, Park, Seongbeom, Choe, Yeongsim, Park, Yu Hyun, Cheon, Bo Kyoung, Hahn, Alice, Ossenkoppele, Rik, Kim, Hee Jin, Kim, Seonwoo, Yoo, Heejin, Jang, Hyemin, Cho, Soo Hyun, Kim, Seung Joo, Kim, Jun Pyo, Jung, Young Hee, Park, Key-Chung, DeCarli, Charles, Weiner, Michael W, Na, Duk L, and Seo, Sang Won

Subjects
Neurodegenerative, Brain Disorders, Genetics, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Acquired Cognitive Impairment, Aging, Neurosciences, Dementia, Alzheimer's Disease, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Aged, Aged, 80 and over, Alzheimer Disease, Amyloid beta-Peptides, Apolipoprotein E2, Body Burden, Cognitive Dysfunction, Cross-Sectional Studies, Dementia, Vascular, Female, Genetic Predisposition to Disease, Genotype, Heterozygote, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Positron-Emission Tomography, Prevalence, Clinical Sciences, Cognitive Sciences, Neurology & Neurosurgery
Abstract

ObjectiveTo investigate the association between APOE genotype and β-amyloid (Aβ) burden, as measured by PET in patients with subcortical vascular cognitive impairment (SVCI) and those with Alzheimer disease-related cognitive impairment (ADCI).MethodsThis was a cross-sectional study of 310 patients with SVCI and 999 with ADCI. To evaluate the effects of APOE genotype or diagnostic group on Aβ positivity, we performed multivariate logistic regression analyses. Further distinctive underlying features of latent subgroups were examined by employing a latent class cluster analysis approach.ResultsIn comparison with ε3 homozygotes, in the ADCI group, ε2 carriers showed a lower frequency of Aβ positivity (odds ratio [OR] 0.43, 95% confidence interval [CI] 0.23-0.79), while in the SVCI group, ε2 carriers showed a higher frequency of Aβ positivity (OR 2.26, 95% CI 1.02-5.01). In particular, we observed an interaction effect of ε2 carrier status and diagnostic group on Aβ positivity (OR 5.12, 95% CI 1.93-13.56), in that relative to ε3 homozygotes, there were more Aβ-positive ε2 carriers in the SVCI group than in the ADCI group. We also identified latent subgroups of Aβ-positive APOE ε2 carriers with SVCI and Aβ-positive APOE ε4 carriers with ADCI.ConclusionsOur findings suggest that APOE ε2 is distinctly associated with Aβ deposition in patients with SVCI and those with ADCI. Our findings further suggest that there is a distinctive subgroup of Aβ-positive APOE ε2 carriers with SVCI among patients with cognitive impairment.

Published
2020

8. Design of the Prediction Model for Adolescents’ Stress Using Deep Learning

Author

Lee, Hyejoo, Jung, Euihyun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Kim, Hyuncheol, editor, and Kim, Kuinam J., editor

Published
2021
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9. Exploration of a Prediction Model of Aggression in Children Using Bayesian Networks

Author

Lee, Hyejoo, Jung, Euihyun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Kim, Hyuncheol, editor, and Kim, Kuinam J., editor

Published
2021
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10. An Analysis of Annual Changes on the Determining Factors for Teacher Attachment with Random Forest

Author

Lee, Hyejoo, Jung, Euihyun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Kim, Kuinam J., editor, and Kim, Hye-Young, editor

Published
2020
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11. The Misandry Myth : An Inaccurate Stereotype About Feminists’ Attitudes Toward Men

Author

Hopkins-Doyle, Aífe, Petterson, Aino L., Leach, Stefan, Zibell, Hannah, Chobthamkit, Phatthanakit, Binti Abdul Rahim, Sharmaine, Blake, Jemima, Bosco, Cristina, Cherrie-Rees, Kimberley, Beadle, Ami, Cock, Victoria, Greer, Hazel, Jankowska, Antonina, Macdonald, Kaitlin, Scott English, Alexander, Wai Lan YEUNG, Victoria, Asano, Ryosuke, Beattie, Peter, Bernardo, Allan B.I., Boonroungrut, Chinun, Chaudhuri, Anindita, Chien, Chin Lung, Choi, Hoon Seok, Cui, Lixian, Du, Hongfei, Fuji, Kei, Hitokoto, Hidefumi, Iida, Junko, Ishii, Keiko, Jiang, Ding Yu, Jogdand, Yashpal, Lee, Hyejoo J., Mifune, Nobuhiro, Moon, Chanki, Murayama, Aya, Na, Jinkyung, One, Kim, Park, Joonha, Sato, Kosuke, Sharma, Suryodaya, Suh, Eunkook M., Tipandjan, Arun, Sutton, Robbie M., Hopkins-Doyle, Aífe, Petterson, Aino L., Leach, Stefan, Zibell, Hannah, Chobthamkit, Phatthanakit, Binti Abdul Rahim, Sharmaine, Blake, Jemima, Bosco, Cristina, Cherrie-Rees, Kimberley, Beadle, Ami, Cock, Victoria, Greer, Hazel, Jankowska, Antonina, Macdonald, Kaitlin, Scott English, Alexander, Wai Lan YEUNG, Victoria, Asano, Ryosuke, Beattie, Peter, Bernardo, Allan B.I., Boonroungrut, Chinun, Chaudhuri, Anindita, Chien, Chin Lung, Choi, Hoon Seok, Cui, Lixian, Du, Hongfei, Fuji, Kei, Hitokoto, Hidefumi, Iida, Junko, Ishii, Keiko, Jiang, Ding Yu, Jogdand, Yashpal, Lee, Hyejoo J., Mifune, Nobuhiro, Moon, Chanki, Murayama, Aya, Na, Jinkyung, One, Kim, Park, Joonha, Sato, Kosuke, Sharma, Suryodaya, Suh, Eunkook M., Tipandjan, Arun, and Sutton, Robbie M.

Abstract

In six studies, we examined the accuracy and underpinnings of the damaging stereotype that feminists harbor negative attitudes toward men. In Study 1 (n = 1,664), feminist and nonfeminist women displayed similarly positive attitudes toward men. Study 2 (n = 3,892) replicated these results in non-WEIRD countries and among male participants. Study 3 (n = 198) extended them to implicit attitudes. Investigating the mechanisms underlying feminists’ actual and perceived attitudes, Studies 4 (n = 2,092) and 5 (nationally representative UK sample, n = 1,953) showed that feminists (vs. nonfeminists) perceived men as more threatening, but also more similar, to women. Participants also underestimated feminists’ warmth toward men, an error associated with hostile sexism and a misperception that feminists see men and women as dissimilar. Random-effects meta-analyses of all data (Study 6, n = 9,799) showed that feminists’ attitudes toward men were positive in absolute terms and did not differ significantly from nonfeminists'. An important comparative benchmark was established in Study 6, which showed that feminist women's attitudes toward men were no more negative than men's attitudes toward men. We term the focal stereotype the misandry myth in light of the evidence that it is false and widespread, and discuss its implications for the movement.

Published
2024

13. The Misandry Myth: An Inaccurate Stereotype About Feminists’ Attitudes Toward Men

Author

Hopkins-Doyle, Aífe, primary, Petterson, Aino L., additional, Leach, Stefan, additional, Zibell, Hannah, additional, Chobthamkit, Phatthanakit, additional, Binti Abdul Rahim, Sharmaine, additional, Blake, Jemima, additional, Bosco, Cristina, additional, Cherrie-Rees, Kimberley, additional, Beadle, Ami, additional, Cock, Victoria, additional, Greer, Hazel, additional, Jankowska, Antonina, additional, Macdonald, Kaitlin, additional, Scott English, Alexander, additional, Wai Lan YEUNG, Victoria, additional, Asano, Ryosuke, additional, Beattie, Peter, additional, Bernardo, Allan B. I., additional, Boonroungrut, Chinun, additional, Chaudhuri, Anindita, additional, Chien, Chin-Lung, additional, Choi, Hoon-Seok, additional, Cui, Lixian, additional, Du, Hongfei, additional, Fuji, Kei, additional, Hitokoto, Hidefumi, additional, Iida, Junko, additional, Ishii, Keiko, additional, Jiang, Ding-Yu, additional, Jogdand, Yashpal, additional, Lee, Hyejoo J., additional, Mifune, Nobuhiro, additional, Moon, Chanki, additional, Murayama, Aya, additional, Na, Jinkyung, additional, One, Kim, additional, Park, Joonha, additional, Sato, Kosuke, additional, Sharma, Suryodaya, additional, Suh, Eunkook M., additional, Tipandjan, Arun, additional, and Sutton, Robbie M., additional

Published
2023
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22. Video Fingerprinting System Using Wavelet and Error Correcting Code

Author

Kang, Hyunho, Kurkoski, Brian, Park, Youngran, Lee, Hyejoo, Shin, Sanguk, Yamaguchi, Kazuhiko, Kobayashi, Kingo, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Song, Joo-Seok, editor, Kwon, Taekyoung, editor, and Yung, Moti, editor

Published
2006
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23. Validation of Korean Version of Comprehensive Meaningful Work Scale

Author

Park, Yonguk, Seol, Jeong Hoon, Choi, Jinsoo, Lee, Hyejoo, and Sohn, Young Woo

Subjects
scale validation, 다차원적 일 의미감 척도, comprehensive meaningful work scale, 척도 번안타당화, work meaning, work meaningfulnesss, scale translation, 일 의미감
Abstract

Despite the steadily increasing social and academic interest in work meaningfulness, access to this concept as a psychological construct remains insufficient. This study aimed to provide reliable and valid measurement of work meaningfulness for Korean employees by adapting the CMWS, a scale developed by Lips-Wiersma and Wright(2012), into Korean. To verify its validity, data for 516 full-time Korean employees were randomly divided into two groups, and exploratory and confirmatory factor analyses were conducted. The analyses confirmed that the K-CMWS is a seven-factor structural model as shown in the original scale development study. In addition, by using the entire sample, the relationship between the CMWS and major variables related to work and life domains was verified for convergent and criterion validity. Finally, as a result of performing hierarchical regression analysis to verify the incremental validity of the CMWS for major job and organization-related outcome variables. The CMWS confirmed a significant incremental explanatory amount even while controlling for the existing work meaningfulness scales., 일 의미감(work meaningfulness)에 대한 사회 및 학문적 관심이 지속적으로 증가하고 있음에도 불구하고, 심리학적 구성개념으로서의 일 의미감에 대한 접근은 부족한 실정이다. 본 연구의 목적은 일 의미감을 7개의 심리적 구성요소로 구분하여 체계화한 Lips-Wiersma와 Wright(2012)의 다차원적 일 의미감 척도(Comprehensive Meaningful Work Scale; CMWS)를 한국어로 번안 및 타당화하는 것이다. 국내 남녀 정규직 직장인 516명의 데이터를 2개의 무작위 표본으로 구분하여 탐색적 요인분석과 확인적 요인분석을 실시하였다. 분석결과 원척도 타당화 연구에서 제안한 바와 같이 7요인 구조모형임을 확인하였다. 또한 전체 표본을 활용하여 CMWS와 직무 및 삶 관련 주요변인 간의 관계를 확인하여 수렴 타당도, 준거 타당도 및 변별 타당도를 검증하였다. 마지막으로 주요 직무 및 조직관련 결과변인에 대하여 CMWS의 증분 타당도를 검증하기 위한 위계적 회귀분석을 실시한 결과, CMWS는 기존의 일 의미감 척도를 통제하고도 유의한 증분 설명량을 가지는 것을 확인하였다. 이를 통해 K-CMWS가 가지는 신뢰도 및 타당도를 확인하였으며, 본 연구의 의의와 한계점, 그리고 추후 연구를 위한 제언 등을 논의하였다.

Published
2022
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25. Factors Affecting Problem Finding Depending on Degree of Structure of Problem Situation

Author

Lee, Hyejoo and Cho, Younsoon

Abstract

The authors identified factors affecting problem finding depending on degree of structure of problem situation--either ill or moderately structured. Fifth-grade students (N = 115) were randomly assigned to 2 groups: Group 1 (n = 60) accomplished the ill-structured task; Group 2 (n = 55) performed the moderately structured task. Results indicated that the degree of structure of problem situation influenced variables affecting problem finding. In the ill-structured problem situation, scientific knowledge and personality traits positively affected problem finding, and divergent thinking negatively affected problem finding. In the moderately structured problem situation, divergent thinking and intrinsic motivation positively affected problem finding. Findings suggest that considering the degree of structure of problem situation helps teachers compose instruction methods to enhance students' problem-finding performance. (Contains 6 tables.)

Published
2007
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28. Additional file 1 of Predicting conversion of brain β-amyloid positivity in amyloid-negative individuals

Author

Park, Chae Jung, Seo, Younghoon, Choe, Yeong Sim, Jang, Hyemin, Lee, Hyejoo, and Kim, Jun Pyo

Abstract

Additional file 1: Supplementary Table 1. Model performances according to different cutoff for follow-up duration. Supplementary Table 2. Model performances according to different Aβ cutoff values. Supplementary Figure 1. Longitudinal β-amyloid positivity trajectories. Amyloid tracer uptake values versus follow-up years are plotted for (A) Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset and (B) Samsung Medical Center (SMC) dataset. Trajectory of converters are colored in scarlet, whereas non-converters are colored in gray. The dotted horizonal line is the cutoff for β-amyloid positivity, where SUVR 1.11 for ADNI and Centiloid of 20 for SMC dataset, respectively.

Published
2022
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32. Potential Applications of Artificial Intelligence in Clinical Trials for Alzheimer’s Disease

Author

Seo, Younghoon, Jang, Hyemin, and Lee, Hyejoo

Subjects
clinical_neurology
Abstract

Clinical trials for Alzheimer’s disease (AD) face multiple challenges, such as the high screen failure rate and even allocation of heterogeneous participants. Artificial intelligence (AI), which has become a potent tool of modern science with the expansion in the volume, variety, and velocity of biological data, offers promising potential to address these issues in AD clinical trials. In this review, we introduce the current status of AD clinical trials and topic of machine learning. Then, a comprehensive review is focused on the potential applications of AI in the steps of AD clinical trials, including the prediction of AD biomarkers and differential diagnosis of AD in the prescreen during eligibility assessment and the likelihood stratification of patients who will progress to AD dementia and fast cognitive decline group from the slow decline group in randomization. Finally, this review provides challenges, developments and the future outlook on the integration of AI into AD clinical trials.

Published
2021

34. A study on the changes in life habits, mental health, and sleep quality of college students due to COVID-19.

Author

Lee, Hyejoo, Kim, Jiyun, Moon, Jihwan, Jung, Sangyeop, Jo, Younhwan, Kim, Byeongmin, Ryu, Eunseo, and Bahn, Sangwoo

Subjects
HABIT, LIFESTYLES, MENTAL health, T-test (Statistics), RESEARCH funding, QUESTIONNAIRES, CHI-squared test, DESCRIPTIVE statistics, STATISTICS, ANALYSIS of variance, PSYCHOLOGY of college students, SLEEP quality, DELPHI method, DATA analysis software, COVID-19 pandemic, SOCIAL distancing, SOCIAL isolation
Abstract

BACKGROUND: In early 2020, the coronavirus 2019 (COVID-19) pandemic necessitated changes in social behavior to prevent its spread, including holding online classes, implementing social distancing, and allowing employees to telecommute. However, these changes have had a negative impact on people's sleep patterns and mental health, particularly for college students. OBJECTIVE: This study investigated the relationship between mental health and sleep quality according to the changes in lifestyle of college students in the periods before and after COVID-19. METHODS: The study subjects were 164 college students from Korea who had both face-to-face and non-face-to-face college experiences before and after COVID-19. The experiment was conducted using a Google survey, and the participants were recruited from the college community. The general features and lifestyle habits for the individuals were assessed using the AUDIT-K, Delphi method, KGHQ (General Mental Health Scale), and PSQI-K (Pittsburg Sleep Quality Index). RESULTS: The KGHQ and PSQI scores increased with the spread of COVID-19, which means that the mental health and sleep quality of college students deteriorated. 11 categories of variables were further investigated to evaluate changes in lifestyle, and the results indicate significant changes in the number of private meetings per week, monthly drinking, outdoor activity time, electronic device usage time, weekly food delivery, weekly late-night snacks, daily snacks, and daily coffee intake and no significant changes in exercise, smoking, and fast food intake. CONCLUSION: COVID-19 caused many changes in the lifestyle of college students, which adversely affected mental health and sleep. [ABSTRACT FROM AUTHOR]

Published
2022
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40. The Cortical Neuroanatomy Related to Specific Neuropsychological Deficits in Alzheimer's Continuum

Author

Kang, Sung Hoon, primary, Park, Yu Hyun, additional, Lee, Daun, additional, Kim, Jun Pyo, additional, Chin, Juhee, additional, Ahn, Yisuh, additional, Park, Seong Beom, additional, Kim, Hee Jin, additional, Jang, Hyemin, additional, Jung, Young Hee, additional, Kim, Jaeho, additional, Lee, Jongmin, additional, Kim, Ji-Sun, additional, Cheon, Bo Kyoung, additional, Hahn, Alice, additional, Lee, Hyejoo, additional, Na, Duk L., additional, Kim, Young Ju, additional, and Seo, Sang Won, additional

Published
2019
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41. 소명의식과 진로적응성의 관계에서 소명실행의 조절효과: The moderating effects of living a calling

Author

Min, Jihyun J, Kang, Esther, and Lee, Hyejoo J

Abstract

소명을 의식하는 것(“소명의식”)과 소명을 적용하는 것(“소명실행”)은 구분되는 개념으로, 소명을 적용하는 소명실행은 의식하는 소명(소명의식)을 삶에서 실행하는 것이다. 본 연구는 소명실행이 소명의식과 진로적응성의 관계를 조절하는지 성인직장인과 대학생을 대상으로 검증하였다. 우리는 직장인 집단의 경우 소명의식과 진로적응성의 관계가 소명을 실행하는 정도에 따라 달라질 것이라고 예측하였다. 반면에, 현재 직업이 없는 대학생 집단에서는 의식하고 있는 소명을 실천할 수 있는 기회가 제한되기 때문에 소명실행의 정도가 소명의식과 진로적응성의 관계를 조절하지 못할 것으로 예측하였다. 하지만 339명의 성인 직장인과 248명의 대학생을 대상으로 실시 한 본 연구의 결과는 예상했던 것과 다르게 성인 직장인 집단과 대학생 집단 모두에서 소명실행이 소명의식과 진로적응성의 관계를 유의미하게 조절하는 것으로 나타났으며, 두 집단 간의 조절효과 양상에 차이가 있음을 보여주었다. 직장인 집단의 경우, 소명실행은 부적으로 소명의식과 진로적응성의 관계를 조절하였으나 대학생 집단에서는 정적으로 소명실행이 소명의식과 진로적응성의 관계를 조절하는 것으로 나타났다. 따라서 본 연구의 결과는 직업의 유무에 따라서 소명실행이 소명의식과 진로적응성의 관계를 조절하는 양상이 다르다는 것을 보여준다, One’s calling can be divided into cognitive (“perceiving a calling”) and applied phases (“living a calling”), with the latter involving the execution of the former in life. We examined if living a calling moderate the relation between perceiving a calling and career adaptability. We hypothesized that the relation between perceiving a calling and career adaptability will differ according to the degree of calling execution by employees. However, for currently unemployed college students, we hypothesized that the level of calling execution would not influence the aforementioned relationship because they would have fewer opportunities for executing their perceived calling. The study results with 392 adult professionals and 248 college students indicated that living a calling significantly moderated the relation between perceiving a calling and career adaptability, in both adults and students but in opposite direction. Thus, whether one has a job or not, living a calling affect the relationship between perceiving a calling and career adaptability.

Published
2017
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42. A study on the predictive validity of conditional reasoning test for aggression: Interaction effect with self-reported measures

Author

Jeon, Sohyun, Chang, JaeYoon, and Lee, HyeJoo

Abstract

The purpose of this study was to examine the channeling model to investigate the interaction effect of implicit measure (Conditional Reasoning Test for Aggression: CRT-A) and self-reported measure of aggression to predict helping behavior. Expatriates who were dispatched to China or India (N=101) participated in this study. To reduce the common method bias, their host country co-workers (N=320) evaluated the expatriates’ helping behavior as a behavioral criterion. The results showed that there was a significance difference in helping behavior among the expatriates who had high CRT-A scores. Specifically, latent aggressive individuals who consciously perceived themselves as being non-aggressive but implicitly rationalized their aggressive behavior were less likely to show helping behavior. The academic implications of the current study, along with suggestions for the future research, were discussed., 본 연구는 조직시민행동의 한 요인인 도움행동을 예측함에 있어서 암묵적 공격성을 측정하는 조건추론검사(Conditional Reasoning Test for Aggression; CRT-A)와 자기보고형 공격성 측정치의 상호작용 효과를 확인하고자 하였다. 대기업 종사자 중 중국과 인도로 파견된 주재원들 101명을 대상으로, 조건추론검사와 자기보고형 설문지로 암묵적 공격성과 외현적 공격성을 측정하고 공통방법 영향을 최소화하기 위해 주재원들의 현지 동료들로부터 주재원의 도움행동 정도를 설문지를 통하여 수집하였다. 연구 결과, 암묵적 공격성이 높은 사람들은 자신의 외현적 공격성을 인식하는 정도에 따라 도움행동을 보이는 정도에서 차이를 보였는데 자신이 ‘공격적이지 않다’고 인식하는 사람일수록 도움행동을 더 적게 보였다. 구체적으로, CRT-A 점수는 높지만 자기보고형 공격성 점수는 낮은 ‘잠재된 공격성(latent aggressives)’ 집단에서 도움행동을 가장 적게 하는 것으로 나타났다. 본 연구결과를 바탕으로 연구의 시사점및 제한점과 더불어 후속 연구방향에 대해 논의하였다.

Published
2017
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43. Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment.

Author

Kang, Sung Hoon, Cheon, Bo Kyoung, Kim, Ji-Sun, Jang, Hyemin, Kim, Hee Jin, Park, Kyung Won, Noh, Young, Lee, Jin San, Ye, Byoung Seok, Na, Duk L., Lee, Hyejoo, and Seo, Sang Won

Subjects
AMNESTIC mild cognitive impairment, MACHINE learning, RECEIVER operating characteristic curves, POSITRON emission tomography, AMYLOID
Abstract

Background: Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cost and safety issues.Objective: We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers.Methods: We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers).Results: Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity.Conclusion: Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD. [ABSTRACT FROM AUTHOR]

Published
2021
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