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Table · dataset · 2026

Priorities and design principles for a mobile health (mHealth) application to support self-management of post-stroke aphasia: experience gathering and prioritisation within an experience-based co-design approach

Listed in ZivaHub and HKU DataHub and figshare and Loughborough Research Repository and UP Research Data Repository — shown once because both records carry DOI 10.6084/m9.figshare.34022895.v1

<p>(1) To map experiences of accessing and adhering to community-based aphasia therapy and establish priorities for improvement, based on lived experience.

Description

(2) To identify design principles for the experience-based co-design (EBCD) of a mobile health self-management application.</p> <p>EBCD and human-centred design. Experience gathering and prioritisation (stages 1–3) with people with aphasia (<i>n</i> = 13), significant others (<i>n</i> = 8), and health professionals (<i>n</i> = 10) in interviews and focus groups.

Experiences were analysed thematically to identify unmet needs and touchpoints. Priorities were established using the nominal group technique and mapped to technology design principles.</p> <p>Five touchpoints were identified: (1) The great divide; (2) Too many roadblocks; (3) Getting enough therapy that’s right for me; (4) A need to see progress; (5) Finding new ways to bridge the therapy gap. Priorities were synthesised into seven themes and mapped to five design principles: (1) connects the person with aphasia with their speech pathologist, significant others, and community; (2) links goals-therapy-outcomes; (3) shows progress visually; (4) supports information finding and sharing; and (5) is customisable and accessible.</p> <p>A customisable mHealth solution that facilitates connections and information finding, links goals, therapy, and outcomes, and tracks progress over time, may support aphasia self-management.</p> <p></p><p>People with aphasia, their families, and health professionals describe a great divide between hospital and community rehabilitation, marked by poor information flow, disrupted clinical handover, and long periods without therapy.</p><p>Access and adherence to community aphasia therapy depend on accessible information, personally meaningful therapy, visible progress, and connection with clinicians, peers, and family.</p><p>Rehabilitation professionals should introduce self-management skills, resources, and supports early in the care journey, before the person leaves hospital.</p><p>Rehabilitation professionals should make the links between a person’s goals, their therapy, and their outcomes explicit, and should share progress information in an accessible format.</p><p>Rehabilitation professionals should use technology to add to, rather than replace, ongoing contact with a speech pathologist, and should check that any technology they recommend is accessible to the person with aphasia.</p><p></p> <p>People with aphasia, their families, and health professionals describe a great divide between hospital and community rehabilitation, marked by poor information flow, disrupted clinical handover, and long periods without therapy.</p> <p>Access and adherence to community aphasia therapy depend on accessible information, personally meaningful therapy, visible progress, and connection with clinicians, peers, and family.</p> <p>Rehabilitation professionals should introduce self-management skills, resources, and supports early in the care journey, before the person leaves hospital.</p> <p>Rehabilitation professionals should make the links between a person’s goals, their therapy, and their outcomes explicit, and should share progress information in an accessible format.</p> <p>Rehabilitation professionals should use technology to add to, rather than replace, ongoing contact with a speech pathologist, and should check that any technology they recommend is accessible to the person with aphasia.</p>

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Audio 65%
Provenance · 5 source records, 53 field assertions
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ZivaHuboai:figshare.com:article/3402289512 d agoJSON v1
HKU DataHuboai:figshare.com:article/3402289512 d agoJSON v1
figshareoai:figshare.com:article/3402289511 d agoJSON v1
Loughborough Research Repositoryoai:figshare.com:article/3402289511 d agoJSON v1
UP Research Data Repositoryoai:figshare.com:article/3402289511 d agoJSON v1
FieldAssertionExtractorEvidence
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