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Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study

BACKGROUND: This co-design research method details the iterative process developed to identify health professional recommendations for the graphical user interface (GUI) of an artificial intelligence (AI)–enabled risk prediction tool. Driving the decision to include a co-design process is the belief...

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Autores principales: Marlow, Nicholas, Eckert, Marion, Sharplin, Greg, Gwilt, Ian, Carson-Chahhoud, Kristin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502603/
https://www.ncbi.nlm.nih.gov/pubmed/37651166
http://dx.doi.org/10.2196/47717
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author Marlow, Nicholas
Eckert, Marion
Sharplin, Greg
Gwilt, Ian
Carson-Chahhoud, Kristin
author_facet Marlow, Nicholas
Eckert, Marion
Sharplin, Greg
Gwilt, Ian
Carson-Chahhoud, Kristin
author_sort Marlow, Nicholas
collection PubMed
description BACKGROUND: This co-design research method details the iterative process developed to identify health professional recommendations for the graphical user interface (GUI) of an artificial intelligence (AI)–enabled risk prediction tool. Driving the decision to include a co-design process is the belief that choices regarding the aesthetic and functionality of an intervention are best made by its intended users and that engaging these users in its design will promote the tool’s adoption and use. OBJECTIVE: The aim of this research is to identify health professional design and uptake recommendations for the GUI of an AI-enabled predictive risk tool. METHODS: We will hold 3 research phases, each consisting of 2 workshops with health professionals, between mid-2023 and mid-2024. A total of 6 health professionals will be sought per workshop, resulting in a total enrollment of 36 health professionals at the conclusion of the research. A total of 7 workshop activities have been scheduled across the 3 workshops; these include context of use, notifiers, format, AI survey–Likert, prototype, AI survey–written, and testing. The first 6 of these activities will be repeated in each workshop to enable the iterative development and refinement of GUI. The last activity (testing) will be performed in the final workshop to examine health professionals’ thoughts on the final GUI iteration. Qualitative and quantitative results data will be produced from tasks in each research activity. Qualitative data will be examined through inductive thematic analysis or deductive thematic analysis in accordance with the Nonadoption, Abandonment, and Challenges to the Scale-up, Spread, and Sustainability (NASSS) framework; visual data will be examined in accordance with “framework of interactivity;” and quantitative data will be examined using descriptive statistics. RESULTS: Project registration with the Australia and New Zealand Clinical Trial Registry has been requested (#384098). Finalized design recommendations are expected in early to mid-2024, with a results manuscript to be submitted in mid-2024. This research method has human research ethics approval from the South Australian Department of Health and Wellbeing (#2022/HRE00131) as well as from the Human Research Ethics Committee of the University of South Australia (application ID#204143). CONCLUSIONS: Understanding whether an intervention is needed in a particular situation is just the start; designing an intervention so that it is used within that situation is paramount. This co-design process engages end users to create a GUI that includes the aesthetic and functional details they need in a manner that aligns with their existing work practices. Indeed, interventions that fail to do this may be disliked, and at worst, they may be dangerous. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/47717
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spelling pubmed-105026032023-09-16 Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study Marlow, Nicholas Eckert, Marion Sharplin, Greg Gwilt, Ian Carson-Chahhoud, Kristin JMIR Res Protoc Protocol BACKGROUND: This co-design research method details the iterative process developed to identify health professional recommendations for the graphical user interface (GUI) of an artificial intelligence (AI)–enabled risk prediction tool. Driving the decision to include a co-design process is the belief that choices regarding the aesthetic and functionality of an intervention are best made by its intended users and that engaging these users in its design will promote the tool’s adoption and use. OBJECTIVE: The aim of this research is to identify health professional design and uptake recommendations for the GUI of an AI-enabled predictive risk tool. METHODS: We will hold 3 research phases, each consisting of 2 workshops with health professionals, between mid-2023 and mid-2024. A total of 6 health professionals will be sought per workshop, resulting in a total enrollment of 36 health professionals at the conclusion of the research. A total of 7 workshop activities have been scheduled across the 3 workshops; these include context of use, notifiers, format, AI survey–Likert, prototype, AI survey–written, and testing. The first 6 of these activities will be repeated in each workshop to enable the iterative development and refinement of GUI. The last activity (testing) will be performed in the final workshop to examine health professionals’ thoughts on the final GUI iteration. Qualitative and quantitative results data will be produced from tasks in each research activity. Qualitative data will be examined through inductive thematic analysis or deductive thematic analysis in accordance with the Nonadoption, Abandonment, and Challenges to the Scale-up, Spread, and Sustainability (NASSS) framework; visual data will be examined in accordance with “framework of interactivity;” and quantitative data will be examined using descriptive statistics. RESULTS: Project registration with the Australia and New Zealand Clinical Trial Registry has been requested (#384098). Finalized design recommendations are expected in early to mid-2024, with a results manuscript to be submitted in mid-2024. This research method has human research ethics approval from the South Australian Department of Health and Wellbeing (#2022/HRE00131) as well as from the Human Research Ethics Committee of the University of South Australia (application ID#204143). CONCLUSIONS: Understanding whether an intervention is needed in a particular situation is just the start; designing an intervention so that it is used within that situation is paramount. This co-design process engages end users to create a GUI that includes the aesthetic and functional details they need in a manner that aligns with their existing work practices. Indeed, interventions that fail to do this may be disliked, and at worst, they may be dangerous. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/47717 JMIR Publications 2023-08-31 /pmc/articles/PMC10502603/ /pubmed/37651166 http://dx.doi.org/10.2196/47717 Text en ©Nicholas Marlow, Marion Eckert, Greg Sharplin, Ian Gwilt, Kristin Carson-Chahhoud. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 31.08.2023. https://creativecommons.org/licenses/by/4.0/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 Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.
spellingShingle Protocol
Marlow, Nicholas
Eckert, Marion
Sharplin, Greg
Gwilt, Ian
Carson-Chahhoud, Kristin
Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study
title Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study
title_full Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study
title_fullStr Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study
title_full_unstemmed Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study
title_short Graphical User Interface Development for a Hospital-Based Predictive Risk Tool: Protocol for a Co-Design Study
title_sort graphical user interface development for a hospital-based predictive risk tool: protocol for a co-design study
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10502603/
https://www.ncbi.nlm.nih.gov/pubmed/37651166
http://dx.doi.org/10.2196/47717
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