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IRIS Institutional Research Information System - OPENBS Open Archive UniBS
Background: The pandemic presented unique challenges for individuals with autoimmune and rheumatic diseases (AIRDs) due to their underlying condition, the effects of immunosuppressive treatments, and increased vaccine hesitancy.
Objectives: The COVID-19 vaccination in autoimmune diseases (COVAD) study, a series of ongoing, patient self-reported surveys were conceived with the vision of being a unique tool to gather patient perspectives on AIRDs. It involved a multinational, multicenter collaborative effort amidst a global lockdown.
Methods: Leveraging social media as a research tool, COVAD collected data using validated patient-reported outcomes (PROs). The study, comprising a core team, steering committee, and global collaborators, facilitated data collection and analysis. A pilot-tested, validated survey, featuring questions regarding COVID-19 infection, vaccination and outcomes, patient demographics, and PROs was circulated to patients with AIRDs and healthy controls (HCs).
Discussion: We present the challenges encountered during this international collaborative project, including coordination, data management, funding constraints, language barriers, and authorship concerns, while highlighting the measures taken to address them.
Conclusion: Collaborative virtual models offer a dynamic new frontier in medical research and are vital to studying rare diseases. The COVAD study demonstrates the potential of online platforms for conducting large-scale, patient-focused research and underscores the importance of integrating patient perspective into clinical care. Care of patients is our central motivation, and it is essential to recognize their voices as equal stakeholders and valued partners in the study of the conditions that affect them.
Listening to patients, for the patients: The COVAD Study-Vision, organizational structure, and challenges
Joshi M;Darooka N;Saha S;Dyball S;Sen P;Yaadav P;Javaid M;Kadam E;Shinjo SK;Dey D;Cavagna L;Makol A;Gutiérrez CET;Caballero Uribe CV;Kuwana M;Burmester GR;Ziade N;Wincup C;Andreoli L;Parodis I;Tan AL;Guillemin F;Knitza J;Wang G;Dalbeth N;Velikova T;Gracia-Ramos AE;Nikiphorou E;Day J;Chinoy H;Aggarwal R;Agarwal V;Gupta L;Chafia Dahou Makhloufi;Leandro Gabriel Ferreyra Garrott;Valentina Vardanyan;Vidya Sadanand Limaye;Nilesh Srivastav;Jessica Day;A. T. M. Tanveer Hasan;Sreoshy Saha;Marharyta Volkava;Sonam Yangchen;Dimitri Luz Felipe da Silva;Odirlei Andre Monticielo;Samuel Katsuyuki Shinjo;Russka Shumnalieva;Rositsa Svetoslavova Dacheva;Tsvetelina Velikova;Koy Rattanak;Fernando Kemta Lekpa;Océane Landon-Cardinal;Vanessa Ocampo;María Francisca Bozán Pérez;Antonia Valenzuela;Guochun Wang;Ho So;Iris Tang;Edmund KM Wong;Carlos Enrique Toro Gutiérrez;Sebastian Herrera Uribe;Carlo Vinicio Caballero-Uribe;Ivan Padjen;Zeljka Kardum;Konstantinos Parperis;Karen Schreiber;Jossiell Then Báez;Reem Hamdy Abdellatif Mohammed;Hala Mohamed Lotfy;Walaa Abdel Rahman Saleh;Mervat Eissa;Tamer A. Gheita;Carlos Rios;Sandra Meisalu;Becky Abdissa Adugna;Margherita Giannini;Julien Campagne;Alain Meyer;Francis Guillemin;Hannah Labinsky;Gerd-Rüdiger Burmester;Johannes Knitza;Dzifa Dey;Alexandros Panagiotopoulos;Andrea Bran Ordóñez;Melinda Nagy-Vincze;Vikas Agarwal;Bhupen Barman;Yogesh Preet Singh;Arunkumar R. Pande;Esha Kadam;Praggya Yaadav;Parikshit Sen;Jasmine Parihar;Lakshmi M. R.;Manali Sarkar;Suryo Anggoro Kusumo Wibowo;Maryam Masoumi;Avin Maroof;Asal Adnan Redha;Or Aharonov;Marta Mosca;Nicoletta Del Papa;Atzeni Fabiola;Marco Sebastiani;Franco Franceschini;Pier Paolo Sainaghi;Maria Giovanna Danielli;Vincenzo Venerito;Alessandro Giollo;Laura Andreoli;Alessia Alluno;Devis Benfaremo;Valentino Paci;Giovanni Damiani;Elvis Hysa;Matteo Lucchini;Alberto Lo Gullo;Lorenzo Cavagna;Marco Fornaro;Akira Yoshida;Saori Abe;Masataka Kuwana;Ran Nakashima (Sasai);Fatima Alnaimat;Gulzhan Trimova;Dana Bekaryssova;Eugene Kalman Genga;Nelly Ziade;Soad Salem Hashad;Laila Ayoub;Syahrul Sazliyana Shaharir;Tan Chou Luan;Rosalie Magro;Erick Adrian Zamora Tehozol;Ignacio García-De La Torre;Iris J. Colunga-Pedraza;Javier Merayo-Chalico;Deshire Alpizar-Rodriguez;Miguel Angel Saavedra Salinas;Abraham Edgar Gracia-Ramos;Victoria Sadovici-Bobeica;Zulgerel Dandii;Ihsane Hmamouchi;Binit Vaidya;Luis Fernando Perez Garcia;Nicola Dalbeth;Idania Calixta Escalante Mendoza;Christian Mauriel Uriarte Hernandez;Moussa Elh Ibrahim Fanata;Uyiekpen Ima-Edomwonyi;Ibukunoluwa Dedeke;Airenakho Emorinken;Henry Madu Nwankwo;Hakeem Babatunde Olaosebikan;Celestine Okwara;Tralagba Uchechukwu;Batool Hassan;Uzma Rasheed Babur Salim;Nelly Colman Mc Leod;Manuel Francisco Ugarte-Gil;Victor Pimentel-Quiroz;Lisa S. Traboco;Joanna Makowska;Aleksandra Opinc-Rosiak;Marcin Milchert;Luís Sousa Inês;Samar Al Emadi;Cristina Alexandru;Anca Bobircă;Claudia Cobilinschi;Margarita Aleksandrovna Gromova;Mubirigi Alexandre;Lina El Kibbe;Hussein Mohammed Halabi;Rada Miskovic;Anindita Santosa;Desmond Chua;Cristiana Sieiro Santos;Jesús Loarce-Martos;Sergio Prieto-González;Juan Molina-Collada;Chathurika Lakmini Dandeniya;Ahmed Seri Ibrahim Mohamed;Ioannis Parodis;Raphael Micheroli;Lisa Christ;Oliver Distler;Nada Alchama;Yi-Ming Chen;Chih-Wei Tseng;Phonpen Akarawatcharangura;Wanruchada Katchamart;Wafa Hamdi;Döndü Üsküdar Cansu;Reşit Yıldırım;Tugba Izci Duran;Neslihan Gokcen;Myroslava Kulyk;Nesreen Mohamed Ismail Moustafa;Latika Gupta;Hector Chinoy;Elena Nikiphorou;John D. Pauling;Chris Wincup;Ai Lyn Tan;Tania Gudu;Valentina Pucino;Melanie Sloan;Sarah Dyball;James Lilleker;Aurelie Najm;Arvind Nune;Aarat Patel;Shikha Singla;Tulika Chatterjee;Ashima Makol;Mazen Dimachkie;Yurilís Fuentes-Silva;Bich Ngoc Nguyen;Panganani Njobvu;Hugo Alonzo;Carlos Benito Santiago Pastelin;Generoso Guerra Bautista;Enrique Julio Giraldo Ho;Peter Boyd;Linda Kobert;Karen Cheng;Paula Jordan;Kirtida Oza;Ingrid De Groot;Allison Foss;Celia Meyer;Karin Blomkvist Sporre;Annika Broberg Lavén;Veronica Fatura;and Malak Aburas.
2024-01-01
Abstract
Background: The pandemic presented unique challenges for individuals with autoimmune and rheumatic diseases (AIRDs) due to their underlying condition, the effects of immunosuppressive treatments, and increased vaccine hesitancy.
Objectives: The COVID-19 vaccination in autoimmune diseases (COVAD) study, a series of ongoing, patient self-reported surveys were conceived with the vision of being a unique tool to gather patient perspectives on AIRDs. It involved a multinational, multicenter collaborative effort amidst a global lockdown.
Methods: Leveraging social media as a research tool, COVAD collected data using validated patient-reported outcomes (PROs). The study, comprising a core team, steering committee, and global collaborators, facilitated data collection and analysis. A pilot-tested, validated survey, featuring questions regarding COVID-19 infection, vaccination and outcomes, patient demographics, and PROs was circulated to patients with AIRDs and healthy controls (HCs).
Discussion: We present the challenges encountered during this international collaborative project, including coordination, data management, funding constraints, language barriers, and authorship concerns, while highlighting the measures taken to address them.
Conclusion: Collaborative virtual models offer a dynamic new frontier in medical research and are vital to studying rare diseases. The COVAD study demonstrates the potential of online platforms for conducting large-scale, patient-focused research and underscores the importance of integrating patient perspective into clinical care. Care of patients is our central motivation, and it is essential to recognize their voices as equal stakeholders and valued partners in the study of the conditions that affect them.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/599972
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.