3 results
Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): Recruitment, retention, and data availability in a longitudinal remote measurement study
- F. Matcham, D. Leightley, S. Siddi, F. Lamers, K. White, P. Annas, G. De Girolamo, S. Difrancesco, J.M. Haro, M. Horsfall, A. Ivan, G. Lavelle, Q. Li, F. Lombardini, D. Mohr, V. Narayan, C. Oetzmann, B. Penninx, S. Simblett, S. Bruce, R. Nica, T. Wykes, J. Brasen, I. Myin-Germeys, A. Rintala, P. Conde, R. Dobson, A. Folarin, C. Stewart, Y. Ranjan, Z. Rashid, N. Cummins, N. Manyakov, S. Vairavan, M. Hotopf
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- Journal:
- European Psychiatry / Volume 65 / Issue S1 / June 2022
- Published online by Cambridge University Press:
- 01 September 2022, p. S112
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Introduction
Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an exciting opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks.
ObjectivesTo describe the amount of data collected during a multimodal longitudinal RMT study, in an MDD population.
MethodsRADAR-MDD is a multi-centre, prospective observational cohort study. People with a history of MDD were provided with a wrist-worn wearable, and several apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks and cognitive assessments and followed-up for a maximum of 2 years.
ResultsA total of 623 individuals with a history of MDD were enrolled in the study with 80% completion rates for primary outcome assessments across all timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. Data availability across all RMT data types varied depending on the source of data and the participant-burden for each data type. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. 110 participants had > 50% data available across all data types, and thus able to contribute to multiparametric analyses.
ConclusionsRADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible.
DisclosureNo significant relationships.
Evaluating the effectiveness of InDeaTe tool in supporting design for sustainability
- Shakuntala Acharya, Kiran Ghadge, B. S. C. Ranjan, Suman Devadula, Amaresh Chakrabarti
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In today's aggressive global market, innovation is key for success and design solutions require not only to achieve competitive edge, but also to address the growing environmental, social, and economic needs of the community at large. Consideration of these three pillars of sustainability makes a design inclusive, and life cycle thinking is found to be a promising approach across the literature. However, most supports for design address certain facets or aid singular tasks, and the use of design methods and tools, which have the potential to significantly improve the design process, is low due to inappropriate use and selection of these methods. InDeaTe (Innovation Design database and Template) is a holistic, knowledge-driven, computer-based tool for design of sustainable systems, such as products, manufacturing systems andservice systems and has been developed to address and integrate the aspects of sustainability on a singular design platform. It comprises of the generic design process Template that imbibes life cycle thinking into the process by incorporating consideration of every life cycle phase in each design stage, where design activities are performed iteratively. It further supports the design process by aiding the use and selection of appropriate design methods and tools in concurrence with the primary motivation of improving sustainability of the system with the aid of the InDeaTe Design Database. This paper discusses the ontological underpinnings behind the conceptualization of the InDeaTe methodology and the development of the supporting tool. The paper further reports empirical findings from six different case studies conducted for evaluating the effectiveness of InDeaTe tool in supporting design for sustainability (DfS). The results show that InDeaTe tool has potential in supporting DfS.
Contributors
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- By Douglas L. Arnold, Laura J. Balcer, Amit Bar-Or, Sergio E. Baranzini, Frederik Barkhof, Robert A. Bermel, Francois A. Bethoux, Dennis N. Bourdette, Richard K. Burt, Peter A. Calabresi, Zografos Caramanos, Tanuja Chitnis, Stacey S. Cofield, Jeffrey A. Cohen, Nadine Cohen, Alasdair J. Coles, Devon Conway, Stuart D. Cook, Gary R. Cutter, Peter J. Darlington, Ann Dodds-Frerichs, Ranjan Dutta, Gilles Edan, Michelle Fabian, Franz Fazekas, Massimo Filippi, Elizabeth Fisher, Paulo Fontoura, Corey C. Ford, Robert J. Fox, Natasha Frost, Alex Z. Fu, Siegrid Fuchs, Kazuo Fujihara, Kristin M. Galetta, Jeroen J.G. Geurts, Gavin Giovannoni, Nada Gligorov, Ralf Gold, Andrew D. Goodman, Myla D. Goldman, Jenny Guerre, Stephen L. Hauser, Peter B. Imrey, Douglas R. Jeffery, Stephen E. Jones, Adam I. Kaplin, Michael W. Kattan, B. Mark Keegan, Kyle C. Kern, Zhaleh Khaleeli, Samia J. Khoury, Joep Killestein, Soo Hyun Kim, R. Philip Kinkel, Stephen C. Krieger, Lauren B. Krupp, Emmanuelle Le Page, David Leppert, Scott Litwiller, Fred D. Lublin, Henry F. McFarland, Joseph C. McGowan, Don Mahad, Jahangir Maleki, Ruth Ann Marrie, Paul M. Matthews, Francesca Milanetti, Aaron E. Miller, Deborah M. Miller, Xavier Montalban, Charity J. Morgan, Ichiro Nakashima, Sridar Narayanan, Avindra Nath, Paul W. O’Connor, Jorge R. Oksenberg, A. John Petkau, Michael D. Phillips, J. Theodore Phillips, Tammy Phinney, Sean J. Pittock, Sarah M. Planchon, Chris H. Polman, Alexander Rae-Grant, Stephen M. Rao, Stephen C. Reingold, Maria A. Rocca, Richard A. Rudick, Amber R. Salter, Paula Sandler, Jaume Sastre-Garriga, John R. Scagnelli, Dana J. Serafin, Lynne Shinto, Nancy L. Sicotte, Jack H. Simon, Per Soelberg Sørensen, Ryan E. Stagg, James M. Stankiewicz, Lael A. Stone, Amy Sullivan, Matthew Sutliff, Jessica Szpak, Alan J. Thompson, Bruce D. Trapp, Helen Tremlett, Maria Trojano, Orla Tuohy, Rhonda R. Voskuhl, Marc K. Walton, Mike P. Wattjes, Emmanuelle Waubant, Martin S. Weber, Howard L Weiner, Brian G. Weinshenker, Bianca Weinstock-Guttman, Jeffrey L. Winters, Jerry S. Wolinsky, Vijayshree Yadav, E. Ann Yeh, Scott S. Zamvil
- Edited by Jeffrey A. Cohen, Richard A. Rudick
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- Book:
- Multiple Sclerosis Therapeutics
- Published online:
- 05 December 2011
- Print publication:
- 20 October 2011, pp viii-xii
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