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      A Platform to Develop and Apply Digital Methods for Empirical Bioethics Research: Mixed Methods Design and Development Study

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          Abstract

          Background

          The rise of digital methods and computational tools has opened up the possibility of collecting and analyzing data from novel sources, such as discussions on social media. At the same time, these methods and tools introduce a dependence on technology, often resulting in a need for technical skills and expertise. Researchers from various disciplines engage in empirical bioethics research, and software development and similar skills are not usually part of their background. Therefore, researchers often depend on technical experts to develop and apply digital methods, which can create a bottleneck and hinder the broad use of digital methods in empirical bioethics research.

          Objective

          This study aimed to develop a research platform that would offer researchers the means to better leverage implemented digital methods, and that would simplify the process of developing new methods.

          Methods

          This study used a mixed methods approach to design and develop a research platform prototype. I combined established methods from user-centered design, rapid prototyping, and agile software development to iteratively develop the platform prototype. In collaboration with two other researchers, I tested and extended the platform prototype in situ by carrying out a study using the prototype.

          Results

          The resulting research platform prototype provides three digital methods, which are composed of functional components. This modular concept allows researchers to use existing methods for their own experiments and combine implemented components into new methods.

          Conclusions

          The platform prototype illustrates the potential of the modular concept and empowers researchers without advanced technical skills to carry out experiments using digital methods and develop new methods. However, more work is needed to bring the prototype to a production-ready state.

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          Most cited references30

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          Data Structures for Statistical Computing in Python

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            Transformers: State-of-the-Art Natural Language Processing

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              Social science. Computational social science.

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                Author and article information

                Contributors
                Journal
                JMIR Form Res
                JMIR Form Res
                JFR
                JMIR Formative Research
                JMIR Publications (Toronto, Canada )
                2561-326X
                May 2022
                5 May 2022
                : 6
                : 5
                : e28558
                Affiliations
                [1 ] Health Ethics and Policy Lab Department of Health Sciences and Technology ETH Zurich Zurich Switzerland
                Author notes
                Corresponding Author: Manuel Schneider manuel.schneider@ 123456digitalmethods.ch
                Author information
                https://orcid.org/0000-0002-9645-8723
                Article
                v6i5e28558
                10.2196/28558
                9121222
                35511234
                2d397cf3-ae01-4331-ad7e-ccf17e761b80
                ©Manuel Schneider. Originally published in JMIR Formative Research (https://formative.jmir.org), 05.05.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

                History
                : 7 March 2021
                : 16 March 2021
                : 23 March 2021
                : 5 November 2021
                Categories
                Original Paper
                Original Paper

                digital bioethics,digital humanities,digital methods,computational methods,empirical bioethics,research platform,digital health,bioethics,digital platform

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