Objective
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Investigate how non-exclusive, user-centered design can support patients and caregivers in long-term rehabilitation.
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Gain a deeper understanding of the challenges patients and caregivers face during rehabilitation through qualitative research.
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Explore potential design principles for inclusive mHealth solutions that adapt to patient and caregiver needs over time.
Methodology: Case Study & Qualitative Analysis
A qualitative research approach was employed to gain an in-depth understanding of individual experiences. Participants were recruited through a personal network, and data were collected via remotely conducted semi-structured interviews. With participants' consent, audio recordings were made while ensuring that only necessary data were collected in adherence to ethical and privacy considerations. Thematic analysis was applied to systematically organize the data and extract key insights.
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Semi-structured interview questions were designed around four key themes:
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Understanding of rehabilitation – Definitions, expectations, and personal goals.
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Personal experiences – Participants' full narratives of their rehabilitation journey.
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Changes and challenges – Cognitive functions, environmental adaptations, lifestyle shifts, and social relationships.
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Technology use – Preferences, prior experience, and perceived role in rehabilitation.​
Findings & Analysis
Challenges Faced by Patients & Caregivers
This study identified key challenges for both ABI patients and caregivers, focusing on the cognitive, emotional, and social aspects of rehabilitation.
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​Patients
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Cognitive Impairment & Memory Loss: Short-term memory difficulties disrupt daily activities and engagement with media (e.g., books, movies, conversations).
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Anger Regulation Issues: Emotional outbursts impact family relationships, causing stress for both patients and caregivers.
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Social Isolation: Friendships and workplace connections diminish, leading to decreased confidence and self-esteem.
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Caregivers
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Emotional Stress & Burnout: High caregiving demands lead to emotional strain and withdrawal from social activities.
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Lack of Psychological Support: Limited access to professional guidance leaves caregivers feeling overwhelmed.
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Rehabilitation Support Gaps: Current systems focus on immediate recovery but fail to provide long-term development pathways.
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By understanding these challenges, we can develop mHealth solutions that enhance rehabilitation experiences for both groups.​
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Design Implications for mHealth Solutions
Based on the findings, mHealth applications can play a crucial role in supporting long-term rehabilitation by addressing both patient and caregiver needs. The following design considerations have been summarized:
Cognitive & Memory Support – Context-aware reminders and cognitive exercises to aid memory retention and daily arrangement.
Stress Management – Emotional feedback and guidance to support stress management.
Social Integration & Peer Support – Support networks expand by binding individuals with the community through community-based platforms for shared experiences and structured social activities.
Caregiver Well-Being & Support – Online consultation service or referral to other organizations to provide stress management resources, professional guidance, and peer-support channels to reduce emotional burnout.
Adaptive Rehabilitation Plans – Artificial intelligence is utilized for ongoing assessment of recovery progress in cognitive, emotional, and social adaptation, enabling tailored recommendations that support self-development and respond to the needs at different stages.
Accessible & Affordable Solutions – Digital assistant to support financial sustainability over time and ensure accessibility.
Conclusion
This study explores the challenges faced by patients with acquired brain injuries and their caregivers, highlighting the importance of human-centered design in long-term rehabilitation. Findings indicate that patients often struggle with memory impairments, emotional regulation difficulties, and social reintegration, while caregivers experience emotional stress, social isolation, and a lack of psychological support.
The results emphasize the need to view patients and caregivers as an interdependent unit, where both parties influence and support each other throughout recovery. However, current rehabilitation frameworks often fail to address their long-term and evolving needs. By incorporating mHealth solutions that provide personalized memory support, emotional regulation tools, and structured communication channels, to create a more inclusive and adaptable support system.
Future research should explore adaptive digital solutions, explore the potential of AI in cognitive training, and provide more personalized support to different needs. Applied non-exclusive design principles can further promote patient-caregiver-centered healthcare technology, ensuring care consistency and support in the long term.