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Collaborative design of a decision aid for stroke survivors with multimorbidity: a qualitative study in the UK engaging key stakeholders
Abstract
Objectives: Effective secondary stroke prevention strategies are suboptimally used. Novel development of interventions to enable healthcare professionals and stroke survivors to manage risk factors for stroke recurrence are required. We sought to engage key stakeholders in the design and evaluation of an intervention informed by a learning health system approach, to improve risk factor management and secondary prevention for stroke survivors with multimorbidity. Design: Qualitative, including focus groups, semistructured interviews and usability evaluations. Data was audio recorded, transcribed and coded thematically. Participants: Stroke survivors, carers, health and social care professionals, commissioners, policymakers and researchers. Setting: Stroke survivors were recruited from the South London Stroke Register; health and social care professionals through South London general practices and King’s College London (KCL) networks; carers, commissioners, policymakers and researchers through KCL networks. Results: 53 stakeholders in total participated in focus groups, interviews and usability evaluations. Thirty-seven participated in focus groups and interviews, including stroke survivors and carers (n=11), health and social care professionals (n=16), commissioners and policymakers (n=6) and researchers (n=4). Sixteen participated in usability evaluations, including stroke survivors (n=8) and general practitioners (GPs; n=8). Eight themes informed the collaborative design of DOTT (Deciding On Treatments Together), a decision aid integrated with the electronic health record system, to be used in primary care during clinical consultations between the healthcare professional and stroke survivor. DOTT aims to facilitate shared decision-making on personalised treatments leading to improved treatment adherence and risk control. DOTT was found acceptable and usable among stroke survivors and GPs during a series of evaluations. Conclusions: Adopting a user-centred data-driven design approach informed an intervention that is acceptable to users and has the potential to improve patient outcomes. A future feasibility study and subsequent clinical trial will provide evidence of the effectiveness of DOTT in reducing risk of stroke recurrence.
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“First, decision making tasks that involved more than one decision outcome (Porat et al., 2019;M. A. Rahman et al., 2021) and corresponding support from the AI agent.”
From Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review (2025) · cites this paper as Porat et al., 2019
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Gomez, C., Cho, S. M., Ke, S., Huang, C.-M., & Unberath, M. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2024.1521066 · Cited by 209
Metadata
- Authors
- Porat, T., Marshall, I. J., Sadler, E., Vadillo, M. A., McKevitt, C., Wolfe, C. D. A., & Curcin, V.
- Affiliations
- Dyson School of Design Engineering, Imperial College London, London, UK
- School of Population Health and Environmental Sciences, King’s College London, London, UK
- School of Health Sciences, University of Southampton, UK
- Departamento de Psicología Básica, Universidad Autónoma de Madrid, Madrid, Spain
- Venue
- BMJ Open
- Publisher
- BMJ
- Published
- 2019-08
- Volume
- 9
- Issue
- 8
- Pages
- e030385
- ISSN
- 2044-6055
- Cited by
- 27
- References
- 12
- Language
- en
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