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1. The Role of Family in Diabetes Management for Mexican American Adults.

Author

Jordan, Olivia, Benitez, Amanda, Burnet, Deborah, Quinn, Michael, and Baig, Arshiya

Subjects
Mexican American, diabetes self-management, family, type 2 diabetes, Humans, Female, Male, Mexican Americans, Social Support, Diabetes Mellitus, Type 2, Middle Aged, Family, Adult, Focus Groups, Self-Management, Aged, Qualitative Research, Self Care, Interviews as Topic, Motivation, Stress, Psychological
Abstract

Introduction: The purpose of this study was to characterize how family influences diabetes self-management in Mexican American adults. Methods: Data were analyzed from previously collected data that included 34 semi-structured interviews with Hispanic adults with diabetes and six focus groups with 37 adults with diabetes and family members. Themes related to family and diabetes management were identified and analyzed using a modified template approach. Results: Family-related facilitators to T2DM self-management were (1) provides support, (2) provides motivation, and (3) desire to protect family from diabetes. Family-related challenges were (1) lack of support, (2) family responsibilities, and (3) stress related to family. Diabetes education was shared with family members. Family member perspectives on T2DM included (1) not knowing how to help, (2) effect on emotional wellbeing, (3) diabetes affects the whole family, and (4) family provides support. Conclusion: Most participants with T2DM felt supported by family, but many desired more social support and support surrounding dietary changes from family. Many felt family did not understand what living with diabetes meant for them. Most family members wished to learn more about how to help. Future interventions should include family members and teach them supportive strategies to support beneficial diabetes self-management behaviors.

Published
2024

2. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author

Gemini Team, Georgiev, Petko, Lei, Ving Ian, Burnell, Ryan, Bai, Libin, Gulati, Anmol, Tanzer, Garrett, Vincent, Damien, Pan, Zhufeng, Wang, Shibo, Mariooryad, Soroosh, Ding, Yifan, Geng, Xinyang, Alcober, Fred, Frostig, Roy, Omernick, Mark, Walker, Lexi, Paduraru, Cosmin, Sorokin, Christina, Tacchetti, Andrea, Gaffney, Colin, Daruki, Samira, Sercinoglu, Olcan, Gleicher, Zach, Love, Juliette, Voigtlaender, Paul, Jain, Rohan, Surita, Gabriela, Mohamed, Kareem, Blevins, Rory, Ahn, Junwhan, Zhu, Tao, Kawintiranon, Kornraphop, Firat, Orhan, Gu, Yiming, Zhang, Yujing, Rahtz, Matthew, Faruqui, Manaal, Clay, Natalie, Gilmer, Justin, Co-Reyes, JD, Penchev, Ivo, Zhu, Rui, Morioka, Nobuyuki, Hui, Kevin, Haridasan, Krishna, Campos, Victor, Mahdieh, Mahdis, Guo, Mandy, Hassan, Samer, Kilgour, Kevin, Vezer, Arpi, Cheng, Heng-Tze, de Liedekerke, Raoul, Goyal, Siddharth, Barham, Paul, Strouse, DJ, Noury, Seb, Adler, Jonas, Sundararajan, Mukund, Vikram, Sharad, Lepikhin, Dmitry, Paganini, Michela, Garcia, Xavier, Yang, Fan, Valter, Dasha, Trebacz, Maja, Vodrahalli, Kiran, Asawaroengchai, Chulayuth, Ring, Roman, Kalb, Norbert, Soares, Livio Baldini, Brahma, Siddhartha, Steiner, David, Yu, Tianhe, Mentzer, Fabian, He, Antoine, Gonzalez, Lucas, Xu, Bibo, Kaufman, Raphael Lopez, Shafey, Laurent El, Oh, Junhyuk, Hennigan, Tom, Driessche, George van den, Odoom, Seth, Lucic, Mario, Roelofs, Becca, Lall, Sid, Marathe, Amit, Chan, Betty, Ontanon, Santiago, He, Luheng, Teplyashin, Denis, Lai, Jonathan, Crone, Phil, Damoc, Bogdan, Ho, Lewis, Riedel, Sebastian, Lenc, Karel, Yeh, Chih-Kuan, Chowdhery, Aakanksha, Xu, Yang, Kazemi, Mehran, Amid, Ehsan, Petrushkina, Anastasia, Swersky, Kevin, Khodaei, Ali, Chen, Gowoon, Larkin, Chris, Pinto, Mario, Yan, Geng, Badia, Adria Puigdomenech, Patil, Piyush, Hansen, Steven, Orr, Dave, Arnold, Sebastien M. R., Grimstad, Jordan, Dai, Andrew, Douglas, Sholto, Sinha, Rishika, Yadav, Vikas, Chen, Xi, Gribovskaya, Elena, Austin, Jacob, Zhao, Jeffrey, Patel, Kaushal, Komarek, Paul, Austin, Sophia, Borgeaud, Sebastian, Friso, Linda, Goyal, Abhimanyu, Caine, Ben, Cao, Kris, Chung, Da-Woon, Lamm, Matthew, Barth-Maron, Gabe, Kagohara, Thais, Olszewska, Kate, Chen, Mia, Shivakumar, Kaushik, Agarwal, Rishabh, Godhia, Harshal, Rajwar, Ravi, Snaider, Javier, Dotiwalla, Xerxes, Liu, Yuan, Barua, Aditya, Ungureanu, Victor, Zhang, Yuan, Batsaikhan, Bat-Orgil, Wirth, Mateo, Qin, James, Danihelka, Ivo, Doshi, Tulsee, Chadwick, Martin, Chen, Jilin, Jain, Sanil, Le, Quoc, Kar, Arjun, Gurumurthy, Madhu, Li, Cheng, Sang, Ruoxin, Liu, Fangyu, Lamprou, Lampros, Munoz, Rich, Lintz, Nathan, Mehta, Harsh, Howard, Heidi, Reynolds, Malcolm, Aroyo, Lora, Wang, Quan, Blanco, Lorenzo, Cassirer, Albin, Griffith, Jordan, Das, Dipanjan, Lee, Stephan, Sygnowski, Jakub, Fisher, Zach, Besley, James, Powell, Richard, Ahmed, Zafarali, Paulus, Dominik, Reitter, David, Borsos, Zalan, Joshi, Rishabh, Pope, Aedan, Hand, Steven, Selo, Vittorio, Jain, Vihan, Sethi, Nikhil, Goel, Megha, Makino, Takaki, May, Rhys, Yang, Zhen, Schalkwyk, Johan, Butterfield, Christina, Hauth, Anja, Goldin, Alex, Hawkins, Will, Senter, Evan, Brin, Sergey, Woodman, Oliver, Ritter, Marvin, Noland, Eric, Giang, Minh, Bolina, Vijay, Lee, Lisa, Blyth, Tim, Mackinnon, Ian, Reid, Machel, Sarvana, Obaid, Silver, David, Chen, Alexander, Wang, Lily, Maggiore, Loren, Chang, Oscar, Attaluri, Nithya, Thornton, Gregory, Chiu, Chung-Cheng, Bunyan, Oskar, Levine, Nir, Chung, Timothy, Eltyshev, Evgenii, Si, Xiance, Lillicrap, Timothy, Brady, Demetra, Aggarwal, Vaibhav, Wu, Boxi, Xu, Yuanzhong, McIlroy, Ross, Badola, Kartikeya, Sandhu, Paramjit, Moreira, Erica, Stokowiec, Wojciech, Hemsley, Ross, Li, Dong, Tudor, Alex, Shyam, Pranav, Rahimtoroghi, Elahe, Haykal, Salem, Sprechmann, Pablo, Zhou, Xiang, Mincu, Diana, Li, Yujia, Addanki, Ravi, Krishna, Kalpesh, Wu, Xiao, Frechette, Alexandre, Eyal, Matan, Dafoe, Allan, Lacey, Dave, Whang, Jay, Avrahami, Thi, Zhang, Ye, Taropa, Emanuel, Lin, Hanzhao, Toyama, Daniel, Rutherford, Eliza, Sano, Motoki, Choe, HyunJeong, Tomala, Alex, Safranek-Shrader, Chalence, Kassner, Nora, Pajarskas, Mantas, Harvey, Matt, Sechrist, Sean, Fortunato, Meire, Lyu, Christina, Elsayed, Gamaleldin, Kuang, Chenkai, Lottes, James, Chu, Eric, Jia, Chao, Chen, Chih-Wei, Humphreys, Peter, Baumli, Kate, Tao, Connie, Samuel, Rajkumar, Santos, Cicero Nogueira dos, Andreassen, Anders, Rakićević, Nemanja, Grewe, Dominik, Kumar, Aviral, Winkler, Stephanie, Caton, Jonathan, Brock, Andrew, Dalmia, Sid, Sheahan, Hannah, Barr, Iain, Miao, Yingjie, Natsev, Paul, Devlin, Jacob, Behbahani, Feryal, Prost, Flavien, Sun, Yanhua, Myaskovsky, Artiom, Pillai, Thanumalayan Sankaranarayana, Hurt, Dan, Lazaridou, Angeliki, Xiong, Xi, Zheng, Ce, Pardo, Fabio, Li, Xiaowei, Horgan, Dan, Stanton, Joe, Ambar, Moran, Xia, Fei, Lince, Alejandro, Wang, Mingqiu, Mustafa, Basil, Webson, Albert, Lee, Hyo, Anil, Rohan, Wicke, Martin, Dozat, Timothy, Sinha, Abhishek, Piqueras, Enrique, Dabir, Elahe, Upadhyay, Shyam, Boral, Anudhyan, Hendricks, Lisa Anne, Fry, Corey, Djolonga, Josip, Su, Yi, Walker, Jake, Labanowski, Jane, Huang, Ronny, Misra, Vedant, Chen, Jeremy, Skerry-Ryan, RJ, Singh, Avi, Rijhwani, Shruti, Yu, Dian, Castro-Ros, Alex, Changpinyo, Beer, Datta, Romina, Bagri, Sumit, Hrafnkelsson, Arnar Mar, Maggioni, Marcello, Zheng, Daniel, Sulsky, Yury, Hou, Shaobo, Paine, Tom Le, Yang, Antoine, Riesa, Jason, Rogozinska, Dominika, Marcus, Dror, Badawy, Dalia El, Zhang, Qiao, Wang, Luyu, Miller, Helen, Greer, Jeremy, Sjos, Lars Lowe, Nova, Azade, Zen, Heiga, Chaabouni, Rahma, Rosca, Mihaela, Jiang, Jiepu, Chen, Charlie, Liu, Ruibo, Sainath, Tara, Krikun, Maxim, Polozov, Alex, Lespiau, Jean-Baptiste, Newlan, Josh, Cankara, Zeyncep, Kwak, Soo, Xu, Yunhan, Chen, Phil, Coenen, Andy, Meyer, Clemens, Tsihlas, Katerina, Ma, Ada, Gottweis, Juraj, Xing, Jinwei, Gu, Chenjie, Miao, Jin, Frank, Christian, Cankara, Zeynep, Ganapathy, Sanjay, Dasgupta, Ishita, Hughes-Fitt, Steph, Chen, Heng, Reid, David, Rong, Keran, Fan, Hongmin, van Amersfoort, Joost, Zhuang, Vincent, Cohen, Aaron, Gu, Shixiang Shane, Mohananey, Anhad, Ilic, Anastasija, Tobin, Taylor, Wieting, John, Bortsova, Anna, Thacker, Phoebe, Wang, Emma, Caveness, Emily, Chiu, Justin, Sezener, Eren, Kaskasoli, Alex, Baker, Steven, Millican, Katie, Elhawaty, Mohamed, Aisopos, Kostas, Lebsack, Carl, Byrd, Nathan, Dai, Hanjun, Jia, Wenhao, Wiethoff, Matthew, Davoodi, Elnaz, Weston, Albert, Yagati, Lakshman, Ahuja, Arun, Gao, Isabel, Pundak, Golan, Zhang, Susan, Azzam, Michael, Sim, Khe Chai, Caelles, Sergi, Keeling, James, Sharma, Abhanshu, Swing, Andy, Li, YaGuang, Liu, Chenxi, Bostock, Carrie Grimes, Bansal, Yamini, Nado, Zachary, Anand, Ankesh, Lipschultz, Josh, Karmarkar, Abhijit, Proleev, Lev, Ittycheriah, Abe, Yeganeh, Soheil Hassas, Polovets, George, Faust, Aleksandra, Sun, Jiao, Rrustemi, Alban, Li, Pen, Shivanna, Rakesh, Liu, Jeremiah, Welty, Chris, Lebron, Federico, Baddepudi, Anirudh, Krause, Sebastian, Parisotto, Emilio, Soricut, Radu, Xu, Zheng, Bloxwich, Dawn, Johnson, Melvin, Neyshabur, Behnam, Mao-Jones, Justin, Wang, Renshen, Ramasesh, Vinay, Abbas, Zaheer, Guez, Arthur, Segal, Constant, Nguyen, Duc Dung, Svensson, James, Hou, Le, York, Sarah, Milan, Kieran, Bridgers, Sophie, Gworek, Wiktor, Tagliasacchi, Marco, Lee-Thorp, James, Chang, Michael, Guseynov, Alexey, Hartman, Ale Jakse, Kwong, Michael, Zhao, Ruizhe, Kashem, Sheleem, Cole, Elizabeth, Miech, Antoine, Tanburn, Richard, Phuong, Mary, Pavetic, Filip, Cevey, Sebastien, Comanescu, Ramona, Ives, Richard, Yang, Sherry, Du, Cosmo, Li, Bo, Zhang, Zizhao, Iinuma, Mariko, Hu, Clara Huiyi, Roy, Aurko, Bijwadia, Shaan, Zhu, Zhenkai, Martins, Danilo, Saputro, Rachel, Gergely, Anita, Zheng, Steven, Jia, Dawei, Antonoglou, Ioannis, Sadovsky, Adam, Gu, Shane, Bi, Yingying, Andreev, Alek, Samangooei, Sina, Khan, Mina, Kocisky, Tomas, Filos, Angelos, Kumar, Chintu, Bishop, Colton, Yu, Adams, Hodkinson, Sarah, Mittal, Sid, Shah, Premal, Moufarek, Alexandre, Cheng, Yong, Bloniarz, Adam, Lee, Jaehoon, Pejman, Pedram, Michel, Paul, Spencer, Stephen, Feinberg, Vladimir, Xiong, Xuehan, Savinov, Nikolay, Smith, Charlotte, Shakeri, Siamak, Tran, Dustin, Chesus, Mary, Bohnet, Bernd, Tucker, George, von Glehn, Tamara, Muir, Carrie, Mao, Yiran, Kazawa, Hideto, Slone, Ambrose, Soparkar, Kedar, Shrivastava, Disha, Cobon-Kerr, James, Sharman, Michael, Pavagadhi, Jay, Araya, Carlos, Misiunas, Karolis, Ghelani, Nimesh, Laskin, Michael, Barker, David, Li, Qiujia, Briukhov, Anton, Houlsby, Neil, Glaese, Mia, Lakshminarayanan, Balaji, Schucher, Nathan, Tang, Yunhao, Collins, Eli, Lim, Hyeontaek, Feng, Fangxiaoyu, Recasens, Adria, Lai, Guangda, Magni, Alberto, De Cao, Nicola, Siddhant, Aditya, Ashwood, Zoe, Orbay, Jordi, Dehghani, Mostafa, Brennan, Jenny, He, Yifan, Xu, Kelvin, Gao, Yang, Saroufim, Carl, Molloy, James, Wu, Xinyi, Arnold, Seb, Chang, Solomon, Schrittwieser, Julian, Buchatskaya, Elena, Radpour, Soroush, Polacek, Martin, Giordano, Skye, Bapna, Ankur, Tokumine, Simon, Hellendoorn, Vincent, Sottiaux, Thibault, Cogan, Sarah, Severyn, Aliaksei, Saleh, Mohammad, Thakoor, Shantanu, Shefey, Laurent, Qiao, Siyuan, Gaba, Meenu, Chang, Shuo-yiin, Swanson, Craig, Zhang, Biao, Lee, Benjamin, Rubenstein, Paul Kishan, Song, Gan, Kwiatkowski, Tom, Koop, Anna, Kannan, Ajay, Kao, David, Schuh, Parker, Stjerngren, Axel, Ghiasi, Golnaz, Gibson, Gena, Vilnis, Luke, Yuan, Ye, Ferreira, Felipe Tiengo, Kamath, Aishwarya, Klimenko, Ted, Franko, Ken, Xiao, Kefan, Bhattacharya, Indro, Patel, Miteyan, Wang, Rui, Morris, Alex, Strudel, Robin, Sharma, Vivek, Choy, Peter, Hashemi, Sayed Hadi, Landon, Jessica, Finkelstein, Mara, Jhakra, Priya, Frye, Justin, Barnes, Megan, Mauger, Matthew, Daun, Dennis, Baatarsukh, Khuslen, Tung, Matthew, Farhan, Wael, Michalewski, Henryk, Viola, Fabio, Quitry, Felix de Chaumont, Lan, Charline Le, Hudson, Tom, Wang, Qingze, Fischer, Felix, Zheng, Ivy, White, Elspeth, Dragan, Anca, Alayrac, Jean-baptiste, Ni, Eric, Pritzel, Alexander, Iwanicki, Adam, Isard, Michael, Bulanova, Anna, Zilka, Lukas, Dyer, Ethan, Sachan, Devendra, Srinivasan, Srivatsan, Muckenhirn, Hannah, Cai, Honglong, Mandhane, Amol, Tariq, Mukarram, Rae, Jack W., Wang, Gary, Ayoub, Kareem, FitzGerald, Nicholas, Zhao, Yao, Han, Woohyun, Alberti, Chris, Garrette, Dan, Krishnakumar, Kashyap, Gimenez, Mai, Levskaya, Anselm, Sohn, Daniel, Matak, Josip, Iturrate, Inaki, Chang, Michael B., Xiang, Jackie, Cao, Yuan, Ranka, Nishant, Brown, Geoff, Hutter, Adrian, Mirrokni, Vahab, Chen, Nanxin, Yao, Kaisheng, Egyed, Zoltan, Galilee, Francois, Liechty, Tyler, Kallakuri, Praveen, Palmer, Evan, Ghemawat, Sanjay, Liu, Jasmine, Tao, David, Thornton, Chloe, Green, Tim, Jasarevic, Mimi, Lin, Sharon, Cotruta, Victor, Tan, Yi-Xuan, Fiedel, Noah, Yu, Hongkun, Chi, Ed, Neitz, Alexander, Heitkaemper, Jens, Sinha, Anu, Zhou, Denny, Sun, Yi, Kaed, Charbel, Hulse, Brice, Mishra, Swaroop, Georgaki, Maria, Kudugunta, Sneha, Farabet, Clement, Shafran, Izhak, Vlasic, Daniel, Tsitsulin, Anton, Ananthanarayanan, Rajagopal, Carin, Alen, Su, Guolong, Sun, Pei, V, Shashank, Carvajal, Gabriel, Broder, Josef, Comsa, Iulia, Repina, Alena, Wong, William, Chen, Warren Weilun, Hawkins, Peter, Filonov, Egor, Loher, Lucia, Hirnschall, Christoph, Wang, Weiyi, Ye, Jingchen, Burns, Andrea, Cate, Hardie, Wright, Diana Gage, Piccinini, Federico, Zhang, Lei, Lin, Chu-Cheng, Gog, Ionel, Kulizhskaya, Yana, Sreevatsa, Ashwin, Song, Shuang, Cobo, Luis C., Iyer, Anand, Tekur, Chetan, Garrido, Guillermo, Xiao, Zhuyun, Kemp, Rupert, Zheng, Huaixiu Steven, Li, Hui, Agarwal, Ananth, Ngani, Christel, Goshvadi, Kati, Santamaria-Fernandez, Rebeca, Fica, Wojciech, Chen, Xinyun, Gorgolewski, Chris, Sun, Sean, Garg, Roopal, Ye, Xinyu, Eslami, S. M. Ali, Hua, Nan, Simon, Jon, Joshi, Pratik, Kim, Yelin, Tenney, Ian, Potluri, Sahitya, Thiet, Lam Nguyen, Yuan, Quan, Luisier, Florian, Chronopoulou, Alexandra, Scellato, Salvatore, Srinivasan, Praveen, Chen, Minmin, Koverkathu, Vinod, Dalibard, Valentin, Xu, Yaming, Saeta, Brennan, Anderson, Keith, Sellam, Thibault, Fernando, Nick, Huot, Fantine, Jung, Junehyuk, Varadarajan, Mani, Quinn, Michael, Raul, Amit, Le, Maigo, Habalov, Ruslan, Clark, Jon, Jalan, Komal, Bullard, Kalesha, Singhal, Achintya, Luong, Thang, Wang, Boyu, Rajayogam, Sujeevan, Eisenschlos, Julian, Jia, Johnson, Finchelstein, Daniel, Yakubovich, Alex, Balle, Daniel, Fink, Michael, Agarwal, Sameer, Li, Jing, Dvijotham, Dj, Pal, Shalini, Kang, Kai, Konzelmann, Jaclyn, Beattie, Jennifer, Dousse, Olivier, Wu, Diane, Crocker, Remi, Elkind, Chen, Jonnalagadda, Siddhartha Reddy, Lee, Jong, Holtmann-Rice, Dan, Kallarackal, Krystal, Liu, Rosanne, Vnukov, Denis, Vats, Neera, Invernizzi, Luca, Jafari, Mohsen, Zhou, Huanjie, Taylor, Lilly, Prendki, Jennifer, Wu, Marcus, Eccles, Tom, Liu, Tianqi, Kopparapu, Kavya, Beaufays, Francoise, Angermueller, Christof, Marzoca, Andreea, Sarcar, Shourya, Dib, Hilal, Stanway, Jeff, Perbet, Frank, Trdin, Nejc, Sterneck, Rachel, Khorlin, Andrey, Li, Dinghua, Wu, Xihui, Goenka, Sonam, Madras, David, Goldshtein, Sasha, Gierke, Willi, Zhou, Tong, Liu, Yaxin, Liang, Yannie, White, Anais, Li, Yunjie, Singh, Shreya, Bahargam, Sanaz, Epstein, Mark, Basu, Sujoy, Lao, Li, Ozturel, Adnan, Crous, Carl, Zhai, Alex, Lu, Han, Tung, Zora, Gaur, Neeraj, Walton, Alanna, Dixon, Lucas, Zhang, Ming, Globerson, Amir, Uy, Grant, Bolt, Andrew, Wiles, Olivia, Nasr, Milad, Shumailov, Ilia, Selvi, Marco, Piccinno, Francesco, Aguilar, Ricardo, McCarthy, Sara, Khalman, Misha, Shukla, Mrinal, Galic, Vlado, Carpenter, John, Villela, Kevin, Zhang, Haibin, Richardson, Harry, Martens, James, Bosnjak, Matko, Belle, Shreyas Rammohan, Seibert, Jeff, Alnahlawi, Mahmoud, McWilliams, Brian, Singh, Sankalp, Louis, Annie, Ding, Wen, Popovici, Dan, Simicich, Lenin, Knight, Laura, Mehta, Pulkit, Gupta, Nishesh, Shi, Chongyang, Fatehi, Saaber, Mitrovic, Jovana, Grills, Alex, Pagadora, Joseph, Petrova, Dessie, Eisenbud, Danielle, Zhang, Zhishuai, Yates, Damion, Mittal, Bhavishya, Tripuraneni, Nilesh, Assael, Yannis, Brovelli, Thomas, Jain, Prateek, Velimirovic, Mihajlo, Akbulut, Canfer, Mu, Jiaqi, Macherey, Wolfgang, Kumar, Ravin, Xu, Jun, Qureshi, Haroon, Comanici, Gheorghe, Wiesner, Jeremy, Gong, Zhitao, Ruddock, Anton, Bauer, Matthias, Felt, Nick, GP, Anirudh, Arnab, Anurag, Zelle, Dustin, Rothfuss, Jonas, Rosgen, Bill, Shenoy, Ashish, Seybold, Bryan, Li, Xinjian, Mudigonda, Jayaram, Erdogan, Goker, Xia, Jiawei, Simsa, Jiri, Michi, Andrea, Yao, Yi, Yew, Christopher, Kan, Steven, Caswell, Isaac, Radebaugh, Carey, Elisseeff, Andre, Valenzuela, Pedro, McKinney, Kay, Paterson, Kim, Cui, Albert, Latorre-Chimoto, Eri, Kim, Solomon, Zeng, William, Durden, Ken, Ponnapalli, Priya, Sosea, Tiberiu, Choquette-Choo, Christopher A., Manyika, James, Robenek, Brona, Vashisht, Harsha, Pereira, Sebastien, Lam, Hoi, Velic, Marko, Owusu-Afriyie, Denese, Lee, Katherine, Bolukbasi, Tolga, Parrish, Alicia, Lu, Shawn, Park, Jane, Venkatraman, Balaji, Talbert, Alice, Rosique, Lambert, Cheng, Yuchung, Sozanschi, Andrei, Paszke, Adam, Kumar, Praveen, Austin, Jessica, Li, Lu, Salama, Khalid, Kim, Wooyeol, Dukkipati, Nandita, Baryshnikov, Anthony, Kaplanis, Christos, Sheng, XiangHai, Chervonyi, Yuri, Unlu, Caglar, Casas, Diego de Las, Askham, Harry, Tunyasuvunakool, Kathryn, Gimeno, Felix, Poder, Siim, Kwak, Chester, Miecnikowski, Matt, Dimitriev, Alek, Parisi, Aaron, Liu, Dangyi, Tsai, Tomy, Shevlane, Toby, Kouridi, Christina, Garmon, Drew, Goedeckemeyer, Adrian, Brown, Adam R., Vijayakumar, Anitha, Elqursh, Ali, Jazayeri, Sadegh, Huang, Jin, Carthy, Sara Mc, Hoover, Jay, Kim, Lucy, Kumar, Sandeep, Chen, Wei, Biles, Courtney, Bingham, Garrett, Rosen, Evan, Wang, Lisa, Tan, Qijun, Engel, David, Pongetti, Francesco, de Cesare, Dario, Hwang, Dongseong, Yu, Lily, Pullman, Jennifer, Narayanan, Srini, Levin, Kyle, Gopal, Siddharth, Li, Megan, Aharoni, Asaf, Trinh, Trieu, Lo, Jessica, Casagrande, Norman, Vij, Roopali, Matthey, Loic, Ramadhana, Bramandia, Matthews, Austin, Carey, CJ, Johnson, Matthew, Goranova, Kremena, Shah, Rohin, Ashraf, Shereen, Dasgupta, Kingshuk, Larsen, Rasmus, Wang, Yicheng, Vuyyuru, Manish Reddy, Jiang, Chong, Ijazi, Joana, Osawa, Kazuki, Smith, Celine, Boppana, Ramya Sree, Bilal, Taylan, Koizumi, Yuma, Xu, Ying, Altun, Yasemin, Shabat, Nir, Bariach, Ben, Korchemniy, Alex, Choo, Kiam, Ronneberger, Olaf, Iwuanyanwu, Chimezie, Zhao, Shubin, Soergel, David, Hsieh, Cho-Jui, Cai, Irene, Iqbal, Shariq, Sundermeyer, Martin, Chen, Zhe, Bursztein, Elie, Malaviya, Chaitanya, Biadsy, Fadi, Shroff, Prakash, Dhillon, Inderjit, Latkar, Tejasi, Dyer, Chris, Forbes, Hannah, Nicosia, Massimo, Nikolaev, Vitaly, Greene, Somer, Georgiev, Marin, Wang, Pidong, Martin, Nina, Sedghi, Hanie, Zhang, John, Banzal, Praseem, Fritz, Doug, Rao, Vikram, Wang, Xuezhi, Zhang, Jiageng, Patraucean, Viorica, Du, Dayou, Mordatch, Igor, Jurin, Ivan, Liu, Lewis, Dubey, Ayush, Mohan, Abhi, Nowakowski, Janek, Ion, Vlad-Doru, Wei, Nan, Tojo, Reiko, Raad, Maria Abi, Hudson, Drew A., Keshava, Vaishakh, Agrawal, Shubham, Ramirez, Kevin, Wu, Zhichun, Nguyen, Hoang, Liu, Ji, Sewak, Madhavi, Petrini, Bryce, Choi, DongHyun, Philips, Ivan, Wang, Ziyue, Bica, Ioana, Garg, Ankush, Wilkiewicz, Jarek, Agrawal, Priyanka, Guo, Danhao, Xue, Emily, Shaik, Naseer, Leach, Andrew, Khan, Sadh MNM, Wiesinger, Julia, Jerome, Sammy, Chakladar, Abhishek, Wang, Alek Wenjiao, Ornduff, Tina, Abu, Folake, Ghaffarkhah, Alireza, Wainwright, Marcus, Cortes, Mario, Liu, Frederick, Maynez, Joshua, Terzis, Andreas, Samangouei, Pouya, Mansour, Riham, Kępa, Tomasz, Aubet, François-Xavier, Algymr, Anton, Banica, Dan, Weisz, Agoston, Orban, Andras, Senges, Alexandre, Andrejczuk, Ewa, Geller, Mark, Santo, Niccolo Dal, Anklin, Valentin, Merey, Majd Al, Baeuml, Martin, Strohman, Trevor, Bai, Junwen, Petrov, Slav, Wu, Yonghui, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeffrey, and Vinyals, Oriol

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

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.

Published
2024

9. The Uncertain Pathway from Youth to a Good Job: How Limits to Educational Affordability, Work-Based Learning, and Career Counseling Impede Progress toward Good Jobs

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Campbell, Kathryn Peltier, Cheah, Ban, Gulish, Artem, Quinn, Michael C., and Strohl, Jeff

Abstract

The propensity to believe that good things are likely to happen fuels the enduring belief in the American Dream, including the expectation that each generation will enjoy a better quality of life than the previous one. This report is part of a series on young people's pathways to good jobs. In it, the researchers examine how the route from youth dependency to economic independence in young adulthood has changed over time. It explores how the likelihood of having a good job is affected by (1) educational attainment; (2) field of study; (3) occupation; (4) full-time work; (5) access to high-quality work-based learning; and (6) socioeconomic status. These elements work together to perpetuate inequality of opportunity for young Americans. In this report, the researchers focus on overall historical trends and socioeconomic gaps in opportunity. [For the companion report, "The Uncertain Pathway from Youth to a Good Job: How Racial and Gender Bias Impede Progress toward Good Jobs," see ED624516.]

Published
2022

12. A multitiered analysis platform for genome sequencing: Design and initial findings of the Australian Genomics Cardiovascular Disorders Flagship

Author

Ades, Lesley, Enriquez, Annabel, McLean, Alison, Smyth, Renee, Alankarage, Dimithu, Fatkin, Diane, McNamara, James, Soka, Magdalena, Morgan almog, Fear, Vanessa, Medi, Caroline, Stark, Zornitza, Al-Shinnag, Mohammad, Fine, Miriam, Metke, Alejandro, Sy, Raymond, Atherton, John J., Finlay, Keri, Milnes, Di, Tang, Dotti, Austin, Rachel, Garza, Denisse, Milward, Michael, Taylor, Jessica, Bagnall, Richard D., Giannoulatou, Eleni, Morrish, Ansley, Taylor, Shelby, Barnett, Chris, Gongolidis, Laura, Morwood, Jim, Tchan, Michel, Blue, Gillian M., Gray, Belinda, Mountain, Helen, Thompson, Tina, Bodek, Simon, Greer, Cassie, Mowat, David, Thorpe, Jordan, Boggs, Kirsten, Haan, Eric, Ng, Chai-Ann, Trainer, Alison, Bogwitz, Michael, Haas, Mathilda, Nowak, Natalie, Trivedi, Gunjan, Boughtwood, Tiffany, Hanna, Bernadette, Martinez, Noelia Nunez, Valente, Giulia, Bray, Alessandra, Harvey, Richard, Ohanian, Monique, van Spaendonck-Zwarts, Karin, Brion, Marie-Jo, Hayward, Janette, O’Sullivan, Sinead, Vandenberg, Jamie, Brown, Jaye, Herrera, Carmen, Overkov, Angela, Verma, Kunal, Richardson, Rob Bryson, Hill, Adam, Pachter, Nicholas, Vidgen, Miranda, Burnett, Leslie, Hollingsworth, Georgie, Patel, Chirag, Vohra, Jitendra, Burns, Charlotte, Hollway, Georgina, Perrin, Mark, Waddel-Smith, Kathryn, Cao, Michelle, Horton, Ari E., Perry, Matthew, Wallis, Mathew, Carr, Will, Howting, Denise, Pflaumer, Andreas, Weintraub, Robert G., Casauria, Sarah, Ingles, Jodie, Phillips, Peta, Wilson, Meredith, Chalinor, Heather, Isbister, Joanne, Phuong, Thuan, Winlaw, David, Chang, Yuchen, Jackson, Matilda, Pope-Couston, Rachel, Worgan, Lisa, Chapman, Gavin, James, Paul, Poplawski, Nicola K., Wornham, Linda, Charitou, Theosodia, Jane-Pantaleo, Sarah, Punni, Preeti, Wu, Kathy, Chong, Belinda, Johnson, Renee, Quinn, Michael C.J., Yeates, Laura, Collins, Felicity, Kelly, Andrew, Quinn, Michael, Zentner, Dominica, Correnti, Gemma, King-Smith, Sarah, Rajagopalan, Sulekha, Cox, Kathy, Kirk, Edwin, Raju, Hariharan, Cunningham, Fiona, Kummerfeld, Sarah, Rath, Emma M., Das, Debjani, Lassman, Timo, Regan, Matthew, Davis, Jason, Lipton, Jonathon, Rogers, Jonathan, Davis, Andrew, Lunke, Sebastian, Ryan, Mark, De Fazio, Paul, Macciocca, Ivan, Sandaradura, Sarah, de Silva, Michelle, MacIntyre, Paul, Schonrock, Nicole, Den Elzen, Nicola, Madelli, Evanthia O., Scuffham, Paul, Devery, Sophie, Mallawaarachchi, Amali, Semsarian, Chris, Dobbins, Julia, Mansour, Julia, Sherburn, Isabella, Dunwoodie, Sally L., Martin, Ellenore, Sherlock, Mary-Clare, Dwyer, Nathan, Mathew, Jacob, Singer, Emma, Elbracht-Leong, Stefanie, Mattiske, Tessa, Smerdon, Carla, Elliott, David, McGaughran, Julie, Smith, Janine, Brown, Jaye S., Haas, Matilda, and Pantaleo, Sarah-Jane

Published
2024
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13. The Monetary Value of Economic and Racial Justice in Postsecondary Education: Quantifying the Potential for Public Good

Author

Postsecondary Value Commission, Carnevale, Anthony P., Campbell, Kathryn Peltier, Cheah, Ban, Fasules, Megan L., Gulish, Artem, Quinn, Michael C., Sablan, Jenna R., Smith, Nicole, Strohl, Jeff, and Barrese, Sarah

Abstract

In this report, we present the results of a thought experiment in which we estimated the potential costs and benefits to society of achieving equality in educational attainment and related workforce outcomes by race/ethnicity, class, and gender. We conducted this thought experiment to clarify the role that education can play in reducing inequality. While education has significant value that cannot be measured in monetary terms, we focused in our analysis on monetary outcomes such as earnings, tax revenue, and effects on GDP, along with secondary effects on incarceration costs, public health expenditures, and other public programs, using a stepwise analysis to simulate what would happen if various income, racial or ethnic, and gender equity gaps were closed. We first measured the effect of closing attainment gaps by earnings and race within the population so that low-income adults (those without earnings and those in the bottom 40 percent of earnings) matched the educational attainment of adults in the top 60 percent of earnings, and so that adults from underrepresented racial and ethnic groups matched the educational attainment of White adults. We then examined the marginal gains that would be possible if, in addition to closing attainment gaps, we were able to eliminate federal student loan debt for new completers of college credentials. After exploring the gains that could be possible based on increases in attainment and elimination of student debt for low-income additional credential holders, we conducted a stepwise analysis to estimate the earnings gaps that would remain between White men and other race/gender groups at various equity thresholds. For example, we estimated the wealth gaps that would remain after accounting for new potential cumulative savings (accrued as a result of closing earnings gaps), with the constraint that only 55 percent of wealth on average currently comes from self-generated earnings. By focusing on savings as a first step to accumulating wealth, we were able to analyze wealth at the individual level and build a proxy link between education, earnings, and overall wealth accumulation. We found that simply equalizing attainment by earnings and race/ethnicity would result in 30.5 million more people earning a college credential (a certificate or an associate's degree or above), bringing the total share of Americans with a college credential to 63 percent. We found that reaching this target would have an initial cumulative cost of at least $3.97 trillion, but would create annual benefits to society of more than $956 billion in increased tax revenue, increased GDP, reduced public health expenses, reduced criminal justice expenditures, and reduced reliance on public support programs. The personal benefits of these gains translate to $1.03 trillion in additional annual earnings, corresponding with a $3.17 trillion increase in potential cumulative savings over the course of workers' remaining careers. If we were able to equalize attainment without creating additional debt for new low-income completers, the increase in potential cumulative savings would rise even higher, to $3.76 trillion. It's tempting but inaccurate to interpret these numbers as suggesting that the investment we describe here would pay off in slightly more than four years. Our thought experiment assumes that all costs and benefits are realized immediately, but the harsh reality is that neither costs nor benefits would occur instantaneously. In fact, constraints related to capacity, readiness, and efficiency suggest that even in the best-case scenario--in which substantial systemic reforms allowed more low-income students and students from underrepresented racial/ethnic backgrounds to enroll and succeed in the postsecondary education system--it would take at least 34 years just to fill the gaps at various levels of educational attainment. In this scenario, annual benefits would begin to exceed annual costs after more than nine years and would continue to grow until the annual public benefit reached the maximum of $956 billion annually. Even after equalizing attainment, gaps in earnings and wealth could still take generations to close due to unrelenting inequalities in the workforce, the role of intergenerational transmission in maintaining wealth gaps, and deep structural inequalities maintained over hundreds of years though discriminatory policy and practice. Substantial sustained investment will be required for postsecondary education to realize its full potential to contribute to the public good. [For the executive summary, see ED612642.]

Published
2021

14. The Monetary Value of Economic and Racial Justice in Postsecondary Education: Quantifying the Potential for Public Good. Executive Summary

Author

Postsecondary Value Commission, Carnevale, Anthony P., Campbell, Kathryn Peltier, Cheah, Ban, Fasules, Megan L., Gulish, Artem, Quinn, Michael C., Sablan, Jenna R., Smith, Nicole, Strohl, Jeff, and Barrese, Sarah

Abstract

Many Americans would agree that all people should have equal educational opportunity and equal pay for equal work. And yet, inequality in postsecondary education access, college completion, and post-college outcomes such as wages stubbornly persists, along with the impression that achieving equal outcomes would be too expensive and would take too much time to accomplish. A thought experiment that the authors conducted in partnership with the Postsecondary Value Commission demonstrates that equality in postsecondary education would have considerable value to society. While equalizing educational attainment would be costly and time-intensive, balancing the costs with the potential societal benefits shows that an investment in postsecondary equality is money well spent. The top-line finding of the analysis is that equalizing postsecondary educational attainment by economic status and race/ethnicity would require an initial public investment of $3.97 trillion. The fiscal case for the societal value of economic and racial/ethnic justice in postsecondary education is even stronger today than it was before COVID-19 devastated American life. As higher education is forced to rethink its business model, it has the opportunity to more fully realize the potential of educational equity and recommit to enhancing the public good. Racial and economic justice need to be central goals, not secondary concerns or politically correct conceits unsupported by action, as postsecondary institutions reinvent themselves for the current era. [For the full report, see ED612641.]

Published
2021

15. The Cost of Economic and Racial Injustice in Postsecondary Education

Author

Georgetown University, Center on Education and the Workforce, Postsecondary Value Commission, Carnevale, Anthony P., Campbell, Kathryn Peltier, Cheah, Ban, Fasules, Megan L., Gulish, Artem, Quinn, Michael C., Sablan, Jenna R., Smith, Nicole, Strohl, Jeff, and Barrese, Sarah

Abstract

In partnership with the Postsecondary Value Commission, we conducted a thought experiment on the costs of inequality in the US education system. Our simulation found that the US economy misses out on $956 billion dollars per year, along with numerous nonmonetary benefits, as a result of postsecondary attainment gaps by economic status and race/ethnicity. "The Cost of Economic and Racial Injustice in Postsecondary Education" finds that closing these gaps would require an initial public investment of at least $3.97 trillion, but the benefits would outweigh the costs over time. Equalizing educational attainment without increasing student debt for low-income adults could also boost GDP by a total of $764 billion annually. [During the writing of this report, Kathryn Peltier Campbell, Ban Cheah, Megan L. Fasules, Artem Gulish, Michael C. Quinn, Jenna R. Sablan, Nicole Smith, and Jeff Strohl received funding from the Institute for Higher Education Policy for work done on behalf of the Bill & Melinda Gates Foundation.]

Published
2021

16. Selective Bias: Asian Americans, Test Scores, and Holistic Admissions

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony, and Quinn, Michael C.

Abstract

Affirmative action critics argue that race-conscious admissions policies are keeping Asian American enrollment numbers unfairly low because Asian American students are held to higher admissions standards than applicants of any other race or ethnicity. "Selective Bias: Asian Americans, Test Scores, and Holistic Admissions" evaluates the common arguments made by them and Students for Fair Admissions, which is suing Harvard University and has lawsuits pending against the University of North Carolina and the University of Texas at Austin over their admissions practices. The report finds no strong evidence of discrimination against Asian American applicants in admissions to highly selective colleges.

Published
2021

18. The Dollars and Sense of Free College. Executive Summary

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Sablan, Jenna R., Gulish, Artem, Quinn, Michael C., and Cinquegrani, Gayle

Abstract

This is the executive summary for the report, "The Dollars and Sense of Free College." Policymakers have debated the specifics of free-college programs--including whether free-college eligibility should extend to students at four-year public colleges as well as community colleges, and whether it should be universal or targeted to low-income and middle-income students. Free-college proposals generally reflect support for some form of publicly funded program that makes college attendance affordable for a majority of students. Joe Biden endorsed a free-college plan that was originally part of the party's platform in the previous election. This plan would make public community colleges tuition-free for all students. It also would make four-year public colleges and universities tuition-free for students with family incomes under $125,000, which would mean that approximately 80 percent of in-state undergraduate students at public four-year colleges and universities would not have to pay tuition. The federal government and state governments would share the costs of this program, with the federal government contributing $2 for every $1 contributed by a state. While the Biden plan has immediate relevance to the 2020 election, there are other ways to design free-college plans. This report discusses a variety of free-college models and assesses their relative costs and benefits. [For the full report, see ED608985.]

Published
2020

19. The Dollars and Sense of Free College

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Sablan, Jenna R., Gulish, Artem, Quinn, Michael C., and Cinquegrani, Gayle

Abstract

Free college has been gaining traction as a public policy option in recent years and has been adopted in some form by at least 15 states. Enthusiasm for the idea has gained momentum with the growing realization that a healthy economy requires a well-educated workforce and that workers benefit immensely from education beyond high school. Indeed, job market data show that 80 percent of jobs leading to middle-class wages call for at least some postsecondary education. Of course, free college is not really free for the taxpayers who will wind up paying for it. Supporters of free college argue that investment in the education system is a public good that yields both economic and noneconomic benefits far beyond its costs. In a diverse democratic society, higher education not only provides a path for economic self-sufficiency, it also contributes to positive outcomes such as improved health, reduced crime, and a greater sense of well-being. All these factors might reduce costs to society in the long run. Finally, higher education provides civic value by preparing an educated citizenry to participate in the electoral process. Any assessment of free-college plans needs to consider both costs and benefits. The analysis of a free-college plan endorsed by Joe Biden finds that it would have high costs but would also generate substantial benefits. Biden's plan would allow all students at community colleges and students with family incomes under $125,000 at public four-year universities to attend college without paying tuition. Like other first-dollar plans, Biden's program would allow students to use their existing financial aid toward other attendance costs, such as room and board. Biden's proposal for tuition-free college would cost $49.6 billion in its first year, with $33.1 billion in federal spending and $16.5 billion in state spending. These costs are $8.6 billion less than the costs associated with a first-dollar plan that would cover all students regardless of their family income. This report also examines the class and racial equity implications of first-dollar programs with universal eligibility, the Biden plan, and last-dollar programs with universal eligibility and discusses a variety of free-college models and assesses their relative costs and benefits. [For the executive summary, see ED608988.]

Published
2020

20. The Overlooked Value of Certificates and Associate's Degrees: What Students Need to Know before They Go to College

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Garcia, Tanya I., Ridley, Neil, and Quinn, Michael C.

Abstract

Education beyond high school is now the preferred currency for workers seeking economic opportunity in the US labor market. Since the 1980s, the bachelor's degree has been the gold standard for stable employment and lifetime earnings and the most promising route to the middle class. The new rules of the college and career game confirm that education level matters, and that more education is generally better when it comes to earnings potential. What is less well known is that program of study and major matter even more to potential earnings than education level. As a result, less education can often be worth more. In fact, some certificate holders can earn more than those with an associate's or bachelor's degree, and some associate's degree holders can earn more than those with a bachelor's degree. In other words, certificates and associate's degrees--credentials on the middle-skills pathway--can be viable routes to economic opportunity. Workers who have taken this pathway to jobs are doing so with certificates, associate's degrees, noncredit education, certifications, licenses, and a host of emerging microcredentials such as badges or coding and technology boot camps. But, while pockets of opportunity exist, not enough is known about the risks and rewards of the particular education and training programs available. Today the combined number of certificates and associate's degrees awarded by colleges is roughly equivalent to the number of bachelor's degrees, around 2 million per year, with certificates and associate's degrees each accounting for about 1 million. The students earning the vast majority of these credentials attend public two-year colleges. While certifications, licenses, microcredentials, and noncredit education are also important options on the middle-skills pathway, much less is known about the workforce outcomes of these options because no data source consistently captures this information. Due to limitations in the data, this report focuses on certificates and associate's degrees.

Published
2020

21. Identification of a Locus Near ULK1 Associated With Progression-Free Survival in Ovarian Cancer

Author

Quinn, Michael CJ, McCue, Karen, Shi, Wei, Johnatty, Sharon E, Beesley, Jonathan, Civitarese, Andrew, O'Mara, Tracy A, Glubb, Dylan M, Tyrer, Jonathan P, Armasu, Sebastian M, Ong, Jue-Sheng, Gharahkhani, Puya, Lu, Yi, Gao, Bo, Patch, Ann-Marie, Fasching, Peter A, Beckmann, Matthias W, Lambrechts, Diether, Vergote, Ignace, Edwards, Digna R Velez, Beeghly-Fadiel, Alicia, Benitez, Javier, Garcia, Maria J, Goodman, Marc T, Dörk, Thilo, Dürst, Matthias, Modugno, Francesmary, Moysich, Kirsten, du Bois, Andreas, Pfisterer, Jacobus, Bauman, Klaus, Group, for the AGO Study, Karlan, Beth Y, Lester, Jenny, Cunningham, Julie M, Larson, Melissa C, McCauley, Bryan M, Kjaer, Susanne K, Jensen, Allan, Hogdall, Claus K, Hogdall, Estrid, Schildkraut, Joellen M, Riggan, Marjorie J, Berchuck, Andrew, Cramer, Daniel W, Terry, Kathryn L, Bjorge, Line, Webb, Penelope M, Group, for the OPAL Study, Friedlander, Michael, Pejovic, Tanja, Moffitt, Melissa, Glasspool, Rosalind, May, Taymaa, Ene, Gabrielle EV, Huntsman, David G, Woo, Michelle, Carney, Michael E, Hinsley, Samantha, Heitz, Florian, Fereday, Sian, Kennedy, Catherine J, Edwards, Stacey L, Winham, Stacey J, deFazio, Anna, Group, for Australian Ovarian Cancer Study, Pharoah, Paul DP, Goode, Ellen L, MacGregor, Stuart, and Chenevix-Trench, Georgia

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prevention, Human Genome, Cancer, Genetics, Ovarian Cancer, Rare Diseases, Aetiology, 2.1 Biological and endogenous factors, Autophagy-Related Protein-1 Homolog, Biomarkers, Tumor, Carcinoma, Ovarian Epithelial, Female, Gene Knockout Techniques, Genome-Wide Association Study, Humans, Intracellular Signaling Peptides and Proteins, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Progression-Free Survival, AGO Study Group, OPAL Study Group, for Australian Ovarian Cancer Study Group, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundMany loci have been found to be associated with risk of epithelial ovarian cancer (EOC). However, although there is considerable variation in progression-free survival (PFS), no loci have been found to be associated with outcome at genome-wide levels of significance.MethodsWe carried out a genome-wide association study (GWAS) of PFS in 2,352 women with EOC who had undergone cytoreductive surgery and standard carboplatin/paclitaxel chemotherapy.ResultsWe found seven SNPs at 12q24.33 associated with PFS (P < 5 × 10-8), the top SNP being rs10794418 (HR = 1.24; 95% CI, 1.15-1.34; P = 1.47 × 10-8). High expression of a nearby gene, ULK1, is associated with shorter PFS in EOC, and with poor prognosis in other cancers. SNP rs10794418 is also associated with expression of ULK1 in ovarian tumors, with the allele associated with shorter PFS being associated with higher expression, and chromatin interactions were detected between the ULK1 promoter and associated SNPs in serous and endometrioid EOC cell lines. ULK1 knockout ovarian cancer cell lines showed significantly increased sensitivity to carboplatin in vitro.ConclusionsThe locus at 12q24.33 represents one of the first genome-wide significant loci for survival for any cancer. ULK1 is a plausible candidate for the target of this association.ImpactThis finding provides insight into genetic markers associated with EOC outcome and potential treatment options.See related commentary by Peres and Monteiro, p. 1604.

Published
2021

22. SAT-Only Admission: How Would It Change College Campuses?

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Strohl, Jeff, Van Der Werf, Martin, Quinn, Michael C., and Campbell, Kathryn Peltier

Abstract

Judging from how much high school students and their parents worry about standardized test scores, one might presume that an SAT or ACT score is the primary factor in college admissions. But a look at the numbers reveals a different reality. A review of SAT and ACT standardized test scores among students in a recent class at the nation's 200 most selective colleges finds that if all students were admitted solely on the basis of their test scores and no new seats were added, 53 percent of incoming students at the nation's most selective colleges would no longer be attending. These students had median test scores that were 110 points below the median of all students at selective colleges (1140, compared to 1250). More than half of the students who would be ousted are affluent students-from families in the top quartile of socioeconomic status (SES). The problem however is that if those students were ousted and replaced by applicants with higher test scores, the student bodies of America's most selective colleges would become even more aristocratic. Now, 60 percent of incoming freshmen at selective colleges are from the top quartile of family SES, but that would increase to 63 percent if students were admitted based on standardized test scores alone. In addition to having more affluent students, selective colleges would become notably less racially diverse. The White enrollment would grow by about 14 percent. Meanwhile, the combined Black and Latino enrollment at selective colleges would be reduced by 43 percent, and Asian enrollment would decline as well-by about 9 percent. Researchers performed an thought experiment in which data that followed students entering high school in 2009, which includes information about those students' family socioeconomic status, race and ethnicity, standardized test scores, and college enrollment were examined. Students from the high school class of 2013 who enrolled at the most selective colleges and universities in the country were identified. Then all the prospective college students from that year who reported SAT or ACT scores were reviewed. Researchers sorted by score and took the highest-scoring students until every existing seat was filled in the most selective colleges. After filling all 300,000 existing seats, it was determined that no one with an SAT or SAT-equivalent score below 1250 would have been admitted to the 200 most selective colleges and universities if admissions were based on test scores alone. Findings from this experiment indicated that an SAT-only admissions process isn't the answer. If admission to the most selective colleges were based on SAT scores alone, those institutions would serve even more affluent White students than they already do, further perpetuating intergenerational race and class privilege. Results obtained from this experiment show that the current admissions system disproportionately benefits affluent Whites, and supports the argument that just as an SAT-only admissions standard isn't the answer, neither is an admissions process without any standardization at all. Researchers concluded that what is needed is an admissions system that is not only holistic (while still including some form of standardization), but also transparent. Without transparency, there is no way to ensure that the college admissions system is fair.

Published
2019

23. Born to Win, Schooled to Lose: Why Equally Talented Students Don't Get Equal Chances to Be All They Can Be. Executive Summary

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Fasules, Megan L., Quinn, Michael C., and Campbell, Kathryn Peltier

Abstract

This is the executive summary for the report, "Born to Win, Schooled to Lose: Why Equally Talented Students Don't Get Equal Chances to Be All They Can Be." Throughout their youth, relatively advantaged children enjoy protective and enriched environments that help ensure their success. Meanwhile, equally talented children from poor backgrounds are held back by material disadvantages. Stunningly, a child from the bottom quartile of socioeconomic status who has high test scores in kindergarten has only a 3 in 10 chance of having a college education and a good entry-level job as a young adult, compared to a 7 in 10 chance for a child in the top quartile of socioeconomic status who has low test scores. Thus, the likelihood of success is too often determined not by a child's innate talent, but by his or her life circumstances--including factors that determine access to opportunity based on class, race, and ethnicity. In short, the system conspires against young people from poor families, especially those who are Black or Latino. Among these youth, even those who "make it" and earn a college degree are less likely than their more affluent peers to get a good entry-level job as a young adult. [For the full report, see ED599947.]

Published
2019

24. Born to Win, Schooled to Lose: Why Equally Talented Students Don't Get Equal Chances to Be All They Can Be

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Fasules, Megan L., Quinn, Michael C., and Campbell, Kathryn Peltier

Abstract

In the United States, there is a broadly held presumption that the journey along the pipeline from kindergarten to early career success gradually reveals each child's innate abilities. This presumption is widespread not only in the general public, but among students themselves, who self-identify and identify each other as either academically gifted or generally undistinguished. All too often, these beliefs about one's talents and the talents of one's peers become self-fulfilling prophesies. In this study, the authors test the idea that demonstrated achievement is a perfect reflection of innate ability by tracing children's journeys through and beyond the educational system, from their academic performance in childhood to their early career outcomes as young adults. They find that there is substantial churn in children's demonstrated abilities as they travel through the K-12 system and onward to college and careers. These findings suggest that talent is not fixed: innate ability can be nurtured over time, or it can remain underdeveloped. The education system can play a role in whether children reach their full potential. Their findings also suggest both a good-news and a bad-news story. The good news is that early academic performance is not destiny and that individual striving, educational quality, and policy matter. The bad news is that the existing systems distribute opportunity based on income, class status, race, and ethnicity rather than hard work and talent. As a result, race and class also matter when it comes to children's life chances. [For the executive summary, see ED599950.]

Published
2019

29. Civil Affairs organization in Haiti

Author

Quinn, Michael A., Col and Daniel, Douglas W., Col

Subjects
CIVIL AFFAIRS, PEACEKEEPING - Haiti, UNITED NATIONS MILITARY OBSERVER GROUPS, OPERATION - Maintain Democracy
Abstract

illus chart bibliog

Published
1998

31. Our Separate & Unequal Public Colleges: How Public Colleges Reinforce White Racial Privilege and Marginalize Black and Latino Students. Executive Summary

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Van Der Werf, Martin, Quinn, Michael C., Strohl, Jeff, and Repnikov, Dmitri

Abstract

This is the executive summary for the report, "Our Separate & Unequal Public Colleges: How Public Colleges Reinforce White Racial Privilege and Marginalize Black and Latino Students." America's selective public colleges should be among the great equalizers in our society. Funded primarily by taxpayers and carrying a relatively low price tag, these colleges are meant to be engines of opportunity for all. In reality, however, the doors of these colleges are open wider to White students than to their Black and Latino peers. Whites have almost two-thirds (64%) of the seats in selective public colleges even though Whites make up barely half (54%) of the nation's college-age population. Blacks and Latinos are making unprecedented gains in college-going, but the vast majority of Black and Latino students enroll in overcrowded and underfunded open-access colleges, primarily community colleges. Consequently, fewer Black and Latino students receive a bachelor's degree. [For the full report, see ED594576.]

Published
2018

32. Our Separate & Unequal Public Colleges: How Public Colleges Reinforce White Racial Privilege and Marginalize Black and Latino Students

Author

Georgetown University, Center on Education and the Workforce, Carnevale, Anthony P., Van Der Werf, Martin, Quinn, Michael C., Strohl, Jeff, and Repnikov, Dmitri

Abstract

Since 1980, the Black college-going rate has nearly doubled, while the Latino college-going rate has more than doubled. As a result, the Black and Latino share of public college enrollment has grown from 15 percent in 1980 to 35 percent in 2015. However, those impressive college-going gains are not being matched by gains in college completion. Today, even with their elevated college-going rates, Black and Latino students are only about half as likely as Whites to attain a bachelor's degree or higher. In fact, over the past 35 years, as Black and Latino college-going rates have climbed, the deficit in bachelor's degree attainment between Whites and Blacks and Latinos has actually increased from 15 percentage points to 21 percentage points. A reason for the widening deficit: while White students inordinately attend selective four-year public colleges to pursue bachelor's degrees, Black and Latino students in disproportionate numbers go to open-access public colleges, most of them community colleges where the highest possible credential is an associate's degree. This report tracks levels of minority enrollment and postsecondary expenditures in public colleges by state. Public colleges are exclusively looked at for two major reasons: (1) public colleges collectively enroll more than three out of every four college students, and (2) since public colleges are funded significantly by tax dollars, they have missions that include serving all of their states' residents. [For the executive summary, see ED594582.]

Published
2018

33. Adjuvant chemotherapy following chemoradiotherapy as primary treatment for locally advanced cervical cancer versus chemoradiotherapy alone (OUTBACK): an international, open-label, randomised, phase 3 trial

Author

Mileshkin, Linda R, Moore, Kathleen N, Barnes, Elizabeth H, Gebski, Val, Narayan, Kailash, King, Madeleine T, Bradshaw, Nathan, Lee, Yeh Chen, Diamante, Katrina, Fyles, Anthony W, Small, William, Jr, Gaffney, David K, Khaw, Pearly, Brooks, Susan, Thompson, J Spencer, Huh, Warner K, Mathews, Cara A, Buck, Martin, Suder, Aneta, Lad, Thomas E, Barani, Igor J, Holschneider, Christine H, Van Dyk, Sylvia, Quinn, Michael, Rischin, Danny, Monk, Bradley J, and Stockler, Martin R

Published
2023
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34. Integration of Primary Care and Behavioral Health Services in Midwestern Community Health Centers: A Mixed Methods Study

Author

Staab, Erin M., Wan, Wen, Li, Melissa, Quinn, Michael T., Campbell, Amanda, Gedeon, Stacey, Schaefer, Cynthia T., and Laiteerapong, Neda

Subjects
Medical records -- Analysis, Community health services -- Usage, Behavioral health care -- Methods, Primary health care -- Services, Electronic records -- Analysis, Family and marriage, Health, Psychology and mental health
Abstract

Introduction: Integrating behavioral health (BH) and primary care is an important strategy to improve health behaviors, mental health, and substance misuse, particularly at community health centers (CHCs) where disease burden is high and access to mental health services is low. Components of different integrated BH models are often combined in practice. It is unknown which components distinguish developing versus established integrated BH programs. Method: A survey was mailed to 128 CHCs in 10 Midwestern states in 2016. Generalized estimating equation models were used to assess associations between program characteristics and stage of integration implementation (precontemplation, contemplation, preparation, action, or maintenance). Content analysis of open-ended responses identified integration barriers. Results: Response rate was 60% (N = 77). Most CHCs had colocated BH and primary care services, warm hand-offs from primary care to BH clinicians, shared scheduling and electronic health record (EHR) systems, and depression and substance use disorder screening. Thirty-two CHCs (42%) indicated they had completed integration and were focused on quality improvement (maintenance). Being in the maintenance stage was associated with having a psychologist on staff (odds ratio [OR] = 7.16, 95% confidence interval [CI] [2.76, 18.55]), a system for tracking referrals (OR = 3.42, 95% CI [1.03, 11.36]), a registry (OR = 2.71, 95% CI [1.86, 3.94]), PCMH designation (OR = 2.82, 95% CI [1.48, 5.37]), and a lower proportion of Black/African American patients (OR = .82, 95% CI [.75, .89]). The most common barriers to integration were difficulty recruiting and retaining BH clinicians and inadequate reimbursement. Discussion: CHCs have implemented many foundational components of integrated BH. Future work should address barriers to integration and racial disparities in access to integrated BH. Keywords: behavioral health, primary care, integration, health centers, Nearly one in five adults in the United States experiences a mental health or substance use disorder each year (National Institute of Mental Health, 2019). An important strategy to address [...]

Published
2022
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37. Reanalysis of genomic data in rare disease: current practice and attitudes among Australian clinical and laboratory genetics services

Author

Best, Stephanie, primary, Fehlberg, Zoe, additional, Richards, Christopher, additional, Quinn, Michael C. J., additional, Lunke, Sebastian, additional, Spurdle, Amanda B., additional, Kassahn, Karin S., additional, Patel, Chirag, additional, Vears, Danya F., additional, Goranitis, Ilias, additional, Lynch, Fiona, additional, Robertson, Alan, additional, Tudini, Emma, additional, Christodoulou, John, additional, Scott, Hamish, additional, McGaughran, Julie, additional, and Stark, Zornitza, additional

Published
2024
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43. Assets, Anomalies, and Oddities: Assessing Faculty Perceptions of Nontraditional Scholars with Online Ph.D. Credentials

Author

Quinn, Michael J.

Abstract

Nontraditional scholars with online Ph.D. (NSOP) credentials may encounter skepticism about their credentials, which can be problematic if they opted for the flexibility and accessibility of online graduate education. Faculty members question NSOP motivations, program rigor, and institutional reputation. This study investigates the influence of faculty identity on perceptions of NSOP. This study theorizes that a faculty member's professional, experiential, and demographic identity characteristics influence faculty perceptions of NSOP. To test this theory, tenured and tenure-track faculty at small, private colleges and universities were invited to complete an online survey. Study participants reported their identity characteristics and their perceptions of NSOP expressed as metaphors, and provided optional comments. Metaphorical responses were coded and tested for statistically significant association with identity characteristics using chi-square analysis. Effect sizes were reported. Textual analysis was used to identify themes in participant-provided comments, and semistructured interviews were conducted with a small group of NSOP. The tests of association revealed a small, statistically significant association of perception and identity characteristics, such as the study participants' doctoral type, prior online teaching experience, and prior hybrid teaching experience. The effect sizes for these tests were small. Textual analysis of comments revealed five central themes: the appropriateness of an online Ph.D. for certain academic disciplines, lack of mentoring from faculty, lack of collaboration with peers, suspicion of the level of rigor, and acquiring teaching experience. Interview subjects indicated that they benefited from the ability to conduct quantitative research, enhanced career opportunities, and the diversity of their Ph.D. program peers. This study's results suggest that faculty perceptions of NSOP remain largely negative, but that their perceptions are in flux. The changes may have been influenced by the abrupt transition to online teaching and learning during spring 2020 at the beginning of the COVID-19 pandemic, but understanding the direction and magnitude of the change will require additional study. Barriers for NSOP may have been lowered because more faculty experienced online teaching, but they still exist. The themes identified in participant comments, which exemplify faculty resistance, can serve as a framework for future studies. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2021

44. An Analysis of Vascular Access Thrombosis Events From the Proactive IV irOn Therapy in hemodiALysis Patients Trial

Author

Winnett, Georgia, Akbani, Habib, Winearls, Christopher, Wessels, Julie, Ayub, Waqar, Connor, Andrew, Brown, Alison, Moriarty, Jim, Chowdury, Paramit, Griffiths, Megan, Dasgupta, Indranil, Bhandari, Sunil, Doulton, Timothy, Macdougall, Iain, Barratt, Jonathan, Vilar, Enric, Mitra, Sandip, Ramakrishna, Babu, Nicholas, Johann, Ross, Calum, Khwaja, Arif, Hall, Matt, Kirk, Adam, Smith, Stuart, Jesky, Mark, Day, Clara, Alchi, Bassam, Stratton, Jon, Clarke, Helen, Walsh, Stephen, Brown, Rebecca, McCafferty, Kieran, Solomon, Laurie, Ramadoss, Suresh, Basanyake, Kolitha, Lawman, Sarah, Kalra, Philip, Balasubramaniam, Gowrie, Power, Albert, Banerjee, Debasish, Swift, Pauline, Wellberry-Smith, Matt, Goldsmith, Christopher, Ledson, Thomas, Mikhail, Ashraf, Benzimra, Ruth, Bell, Samira, Severn, Alison, Neary, John, Doyle, Arthur, Thomson, Peter, Shivashankar, Girish, Bolton, Stephanie, Quinn, Michael, Maxwell, Peter, Harty, John, Ford, Ian, Anker, Stefan, Farrington, Kenneth, McMurray, John, Tomson, Charles, Wheeler, David, Petrie, Mark, Connolly, Eugene, Jhund, Pardeep, MacDonald, Michael, Mark, Patrick, Walters, Matthew, Peacock, Janet, Isles, Chris, Reddan, Donal, Aziz, Jane, Boyle, Sarah, Burton, Claire, Clarke, Ross, Dinnett, Eleanor, Hillen, Neil, Kean, Sharon, Kerr, Claire, Murray, Heather, Reid, Amanda, Wetherall, Kirsty, Wilson, Robbie, White, Claire, Andani, Sadiq, Thomson, Peter C., Mark, Patrick B., Robertson, Michele, Anker, Stefan D., Jardine, Alan G., Kalra, Philip A., Wheeler, David C., Winearls, Christopher G., and Macdougall, Iain C.

Published
2022
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45. TEN BRIDGES I'VE BURNT: A Memoir in Verse

Author

Quinn, Michael

Subjects
Literature/writing, Women's issues/gender studies
Abstract

TEN BRIDGES I'VE BURNT A Memoir in Verse by Brontez Purnell MCD. 128 pages, $17. The 38 ballsy, autobiographical poems in Brontez Purnell's Ten Bridges I've Burnt pick apart different [...]

Published
2024

47. Nonoperative Versus Operative Treatment of Z-Type Comminuted Clavicle Fractures in Adolescents: A Prospective Substratified Cohort Analysis.

Author

Sabatini, Coleen S., Edmonds, Eric W., Nepple, Jeffrey J., Liotta, Elizabeth S., Hergott, Katelyn, Quinn, Michael, Perkins, Crystal A., Wilson, Philip L., Ying Li, Ellis, Henry B., Pandya, Nirav K., Pennock, Andrew T., Spence, David D., Willimon, Samuel C., Bae, Donald S., Kocher, Mininder S., Busch, Michael T., Williams, David N., and Heyworth, Benton E.

Published
2024
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50. Assessment of moderate coffee consumption and risk of epithelial ovarian cancer: a Mendelian randomization study

Author

Ong, Jue-Sheng, Hwang, Liang-Dar, Cuellar-Partida, Gabriel, Martin, Nicholas G, Chenevix-Trench, Georgia, Quinn, Michael CJ, Cornelis, Marilyn C, Gharahkhani, Puya, Webb, Penelope M, MacGregor, Stuart, Bryne, Enda, Fasching, Peter A, Hein, Alexander, Burghaus, Stefanie, Beckmann, Matthias W, Lambrechts, Diether, Van Nieuwenhuysen, Els, Vergote, Ignace, Vanderstichele, Adriaan, Swerdlow, Anthony J, Jones, Michael, Orr, Nicholas, Schoemaker, Minouk, Edwards, Digna Velez, Brenton, James, Benítez, Javier, García, María J, Rodriguez-Antona, Cristina, Rossing, Mary Anne, Fortner, Renée T, Riboli, Elio, Chang-Claude, Jenny, Eilber, Ursula, Wang-Gohrke, Shan, Yannoukakos, Drakoulis, Goodman, Marc T, Bogdanova, Natalia, Dörk, Thilo, Duerst, Matthias, Hillemanns, Peter, Runnebaum, Ingo B, Antonenkova, Natalia, Butzow, Ralf, Nevanlinna, Heli, Pelttari, Liisa M, Edwards, Robert P, Kelley, Joseph L, Modugno, Francesmary, Moysich, Kirsten B, Ness, Roberta B, Cannioto, Rikki, Heitz, Florian, Karlan, Beth, Olsson, Håkan, Kjaer, Susanne K, Jensen, Allan, Giles, Graham G, Bruinsma, Fiona, Hildebrandt, Michelle AT, Liang, Dong, Wu, Xifeng, Le Marchand, Loic, Setiawan, V Wendy, Permuth, Jennifer B, Bisogna, Maria, Dao, Fanny, Levine, Douglas A, Cramer, Daniel W, Terry, Kathryn L, Tworoger, Shelley S, Stampfer, Meir, Willet, Walter, Missmer, Stacey, Bjorge, Line, Kopperud, Reidun K, Bischof, Katharina, Thomsen, Liv Cecilie Vestrheim, Kiemeney, Lambertus A, Massuger, Leon FAG, Pejovic, Tanja, Brooks-Wilson, Angela, Olson, Sara H, McGuire, Valerie, Rothstein, Joseph H, Sieh, Weiva, Whittemore, Alice S, Cook, Linda S, Le, Nhu D, Gilks, C Blake, Gronwald, Jacek, Jakubowska, Anna, Lubiński, Jan, Kluz, Tomasz, Wentzensen, Nicolas, Brinton, Louise, Trabert, Britton, and Lissowska, Jolanta

Subjects
Epidemiology, Health Sciences, Clinical Research, Ovarian Cancer, Nutrition, Rare Diseases, Prevention, Cancer, Genetics, 2.1 Biological and endogenous factors, Aetiology, Carcinoma, Ovarian Epithelial, Coffee, Female, Humans, Mendelian Randomization Analysis, Odds Ratio, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Risk Factors, Ovarian Cancer Association Consortium, Statistics, Public Health and Health Services, Public health
Abstract

BackgroundCoffee consumption has been shown to be associated with various health outcomes in observational studies. However, evidence for its association with epithelial ovarian cancer (EOC) is inconsistent and it is unclear whether these associations are causal.MethodsWe used single nucleotide polymorphisms associated with (i) coffee and (ii) caffeine consumption to perform Mendelian randomization (MR) on EOC risk. We conducted a two-sample MR using genetic data on 44 062 individuals of European ancestry from the Ovarian Cancer Association Consortium (OCAC), and combined instrumental variable estimates using a Wald-type ratio estimator.ResultsFor all EOC cases, the causal odds ratio (COR) for genetically predicted consumption of one additional cup of coffee per day was 0.92 [95% confidence interval (CI): 0.79, 1.06]. The COR was 0.90 (95% CI: 0.73, 1.10) for high-grade serous EOC. The COR for genetically predicted consumption of an additional 80 mg caffeine was 1.01 (95% CI: 0.92, 1.11) for all EOC cases and 0.90 (95% CI: 0.73, 1.10) for high-grade serous cases.ConclusionsWe found no evidence indicative of a strong association between EOC risk and genetically predicted coffee or caffeine levels. However, our estimates were not statistically inconsistent with earlier observational studies and we were unable to rule out small protective associations.

Published
2018

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