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Comparison of Clinical Outcomes of Persons Living With HIV by Enrollment Status in Washington, DC: Evaluation of a Large Longitudinal HIV Cohort Study

Jenevieve Opoku, Rupali K Doshi, Amanda D Castel, Ian Sorensen, Michael Horberg, Adam Allston, Michael Kharfen, Alan E Greenberg

JMIR Public Health Surveill 2020;6(2):e16061

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Household Transmission of Zoonotic Influenza Viruses in a Cohort of Egyptian Poultry Growers

Our cohort of poultry-exposed subjects will be assembled from villages from 4 governorates in this area, as well as one governorate south of Cairo, where human cases of AIV were also reported (Figure 1 shows this).

Amira S El Rifay, Mona A Elabd, Dina Abu Zeid, Mokhtar R Gomaa, Li Tang, Pamela P McKenzie, Richard J Webby, Mohamed A Ali, Ghazi Kayali

JMIR Res Protoc 2015;4(2):e74

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Comparison Between a Self-Administered and Supervised Version of a Web-Based Cognitive Test Battery: Results From the NutriNet-Santé Cohort Study

during the Cards task.Design of the Comparison Study In order to compare the self-administered mode of the Nutri Cog Web-based cognitive battery to a supervised mode of this same battery, we conducted a comparison study in a subsample of the Nutri Net-Santé cohort

Karen E Assmann, Marion Bailet, Amandine C Lecoffre, Pilar Galan, Serge Hercberg, Hélène Amieva, Emmanuelle Kesse-Guyot

J Med Internet Res 2016;18(4):e68

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Influence of Social Determinants, Lifestyle, Emotional Well-Being and the Use of Unconventional Therapies in Breast Cancer Progression in a Cohort of Women in Barcelona: Protocol for the DAMA Cohort

Thus, the cohort consists of women diagnosed with breast cancer at different phases of disease progression, and with information from the time of diagnosis onward. Candidates for inclusion received a letter from the hospital inviting them to participate.

Rosa Puigpinos-Riera, Xavier Continente, Gemma Serral, Xavi Bargalló, Montserrat Doménech, Martín Espinosa-Bravo, Jaume Grau, Francesc Macià, Rafael Manzanera, Margarida Pla, M Jesus Quintana, Maria Sala, Eulalia Vidal

JMIR Res Protoc 2017;6(12):e249

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Metadata Correction of: Lessons Learned From Methodological Validation Research in E-Epidemiology

Emmanuelle Kesse-Guyot, Karen Assmann, Valentina Andreeva, Katia Castetbon, Caroline Méjean, Mathilde Touvier, Benoît Salanave, Valérie Deschamps, Sandrine Péneau, Léopold Fezeu, Chantal Julia, Benjamin Allès, Pilar Galan, Serge Hercberg

JMIR Public Health Surveill 2016;2(2):e163

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Internet-Based Birth-Cohort Studies: Is This the Future for Epidemiology?

Ridvan Firestone, Soo Cheng, Neil Pearce, Jeroen Douwes, Franco Merletti, Costanza Pizzi, Emanuele Pivetta, Franca Rusconi, Lorenzo Richiardi

JMIR Res Protoc 2015;4(2):e71

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Lessons Learned From Methodological Validation Research in E-Epidemiology

Advances in knowledge on health and disease strongly rely on the availability, quality, and comprehensiveness of data from prospective cohort studies with very large population-based samples.

Emmanuelle Kesse-Guyot, Karen Assmann, Valentina Andreeva, Katia Castetbon, Caroline Méjean, Mathilde Touvier, Benoît Salanave, Valérie Deschamps, Sandrine Péneau, Léopold Fezeu, Chantal Julia, Benjamin Allès, Pilar Galan, Serge Hercberg

JMIR Public Health Surveill 2016;2(2):e160

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Mediators of Atherosclerosis in South Asians Living in America: Use of Web-Based Methods for Follow-Up and Collection of Patient-Reported Outcome Measures

It also remains uncertain how participant retention rates may differ, if at all, among participants who are recruited and followed in an Internet-based cohort compared to a traditional cohort study.

Namratha R Kandula, Ankita Puri-Taneja, David E Victorson, Swapna S Dave, Alka M Kanaya, Mark D Huffman

JMIR Res Protoc 2016;5(2):e95

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Paper-Based Versus Web-Based Versions of Self-Administered Questionnaires, Including Food-Frequency Questionnaires: Prospective Cohort Study

Participation in this cohort is only by invitation or registration. Currently, all questionnaires of the SUN cohort can be filled by paper or Web-based questionnaires.

Itziar Zazpe, Susana Santiago, Carmen De la Fuente-Arrillaga, Jorge Nuñez-Córdoba, Maira Bes-Rastrollo, Miguel Angel Martínez-González

JMIR Public Health Surveill 2019;5(4):e11997

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Predicting the Development of Type 2 Diabetes in a Large Australian Cohort Using Machine-Learning Techniques: Longitudinal Survey Study

Lei Zhang, Xianwen Shang, Subhashaan Sreedharan, Xixi Yan, Jianbin Liu, Stuart Keel, Jinrong Wu, Wei Peng, Mingguang He

JMIR Med Inform 2020;8(7):e16850

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