Developing a personalised self-management system for post stroke rehabilitation; utilising a user-centred design methodology

Abstract Purpose: To develop and evaluate an information and communication technology (ICT) solution for a post-stroke Personalised Self-Managed Rehabilitation System (PSMrS). The PSMrS translates current models of stroke rehabilitation and theories underpinning self-management and self-efficacy into an ICT-based system for home-based post-stroke rehabilitation. Methods: The interdisciplinary research team applied a hybrid of health and social sciences research methods and user-centred design methods. This included a series of home visits, focus groups, in-depth interviews, cultural probes and technology biographies. Results: The iterative development of both the content of the PSMrS and the interactive interfaces between the system and the user incorporates current models of post-stroke rehabilitation and addresses the factors that promote self-managed behaviour and self-efficacy such as mastery, verbal persuasion and physiological feedback. Conclusion: The methodological approach has ensured that the interactive technology has been driven by the needs of the stroke survivors and their carers in the context of their journey to both recovery and adaptation. Underpinned by theories of motor relearning, neuroplasticity, self-management and behaviour change, the PSMrS developed in this study has resulted in a personalised system for self-managed rehabilitation, which has the potential to change motor behaviour and promote the achievement of life goals for stroke survivors. Implications for Rehabilitation Radical innovation and the adoption of a self-management paradigm need to be considered as a way of delivering home-based post-stroke rehabilitation. A hybrid of health and social sciences research and user-centred design methods are required to ensure that technology for post-stroke rehabilitation has been driven by the needs of the stroke survivors and their carers. Personalised technology systems for self-managed post-stroke rehabilitation have the potential to change motor behaviour and promote the achievement of life goals for stroke survivors.

[1]  Jane Burridge,et al.  A pilot study to investigate the association between muscle activation patterns, wrist tracking performance and upper limb function in post-stroke hemiplegia , 2009 .

[2]  William W. Gaver,et al.  Design: Cultural probes , 1999, INTR.

[3]  Kadriye Ones,et al.  Quality of life for patients poststroke and the factors affecting it. , 2005, Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association.

[4]  A. Bandura Social Foundations of Thought and Action: A Social Cognitive Theory , 1985 .

[5]  B. Hanna,et al.  Recovery after stroke: a qualitative perspective. , 2001, Journal of quality in clinical practice.

[6]  Peter Wright,et al.  Self management of stroke supported by assistive technology , 2009, 2009 Virtual Rehabilitation International Conference.

[7]  Huiru Zheng,et al.  Knowledge transfer for technology based interventions: Collaboration, development and evaluation , 2012 .

[8]  Luc Noreau,et al.  Long-Term Changes in Participation After Stroke , 2006, Topics in stroke rehabilitation.

[9]  Huiru Zheng,et al.  The provision of feedback through computer-based technology to promote self-managed post-stroke rehabilitation in the home , 2014, Disability and rehabilitation. Assistive technology.

[10]  C. Mathers,et al.  Preventing stroke: saving lives around the world , 2007, The Lancet Neurology.

[11]  Peter Robinson,et al.  Designing inclusive interactions , 2013, Universal Access in the Information Society.

[12]  Fadhel Kaboub Realistic Evaluation , 2004 .

[13]  Sandra Mathison,et al.  Encyclopedia of Evaluation , 2004 .

[14]  Johanne Desrosiers,et al.  Changes in Participation After a Mild Stroke: Quantitative and Qualitative Perspectives , 2007, Topics in stroke rehabilitation.

[15]  Jeff G Konin Introduction to rehabilitation. , 2010, Clinics in sports medicine.

[16]  Barbara A. Wilson,et al.  Rehabilitation Studies Handbook , 1997 .

[17]  Huiru Zheng,et al.  Stroke patients’ utilisation of extrinsic feedback from computer-based technology in the home: a multiple case study realistic evaluation , 2014, BMC Medical Informatics and Decision Making.

[18]  M. Hennerici,et al.  Pathophysiology of Stroke Rehabilitation: The Natural Course of Clinical Recovery, Use-Dependent Plasticity and Rehabilitative Outcome , 2006, Cerebrovascular Diseases.

[19]  Huiru Zheng,et al.  Smart self management: assistive technology to support people with chronic disease , 2010, Journal of telemedicine and telecare.

[20]  S. Wood-Dauphinée,et al.  Activity, participation, and quality of life 6 months poststroke. , 2002, Archives of physical medicine and rehabilitation.

[21]  J. Kleim,et al.  Principles of experience-dependent neural plasticity: implications for rehabilitation after brain damage. , 2008, Journal of speech, language, and hearing research : JSLHR.

[22]  Rose Wiles,et al.  Continuity, transition and participation: Preparing clients for life in the community post-stroke , 2007, Disability and rehabilitation.

[23]  J. Krakauer Motor learning: its relevance to stroke recovery and neurorehabilitation. , 2006, Current opinion in neurology.

[24]  Peter C. Wright,et al.  User-centered design for supporting the self-management of chronic illnesses: an interdisciplinary approach , 2009, PETRA '09.

[25]  Susan Michie,et al.  Developing and Evaluating Complex Interventions , 2015 .

[26]  D. Mclellan,et al.  Rehabilitation Studies Handbook: Introduction to rehabilitation , 1997 .

[27]  Peter C. Wright,et al.  Experience-Centered Design: Designers, Users, and Communities in Dialogue , 2010, Experience-Centered Design.

[28]  Jack Parker,et al.  The experience of living with stroke to inform self-management interventions: a qualitative study , 2015 .

[29]  Alan Cooper,et al.  About Face 3: the essentials of interaction design , 1995 .

[30]  G Foster,et al.  Self-management education programmes by lay leaders for people with chronic conditions. , 2007, The Cochrane database of systematic reviews.

[31]  Carol M Mangione,et al.  Improving the management of chronic disease. , 2007, The New England journal of medicine.

[32]  Anne Mandy,et al.  Changing self-efficacy in individuals following a first time stroke: preliminary study of a novel self-management intervention , 2009, Clinical rehabilitation.

[33]  Jorg Huber,et al.  Supporting People With Long-term Conditions , 2014 .

[34]  Huiru Zheng,et al.  Author ' s response to reviews Title : Stroke patients ' utilisation of extrinsic feedback from computer-based technology in the home : a realistic evaluation , 2013 .

[35]  S. Mawson,et al.  The SMART Rehabilitation System for Stroke Self‐management: Issues and Challenges for Evidence‐based Health Technology Research , 2011 .

[36]  Jack Parker,et al.  An Investigation into Stroke Patients’ Utilisation of Feedback from Computer-based Technology , 2010 .

[37]  C. Wolfe,et al.  Cost-Effectiveness of Stroke Unit Care Followed by Early Supported Discharge , 2009, Stroke.

[38]  E. Keogh,et al.  Technologically-assisted behaviour change: a systematic review of studies of novel technologies for the management of chronic illness , 2009, Journal of telemedicine and telecare.

[39]  K. Lorig,et al.  Self-management education: History, definition, outcomes, and mechanisms , 2003, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[40]  Mark Blythe,et al.  Technology biographies: field study techinques for home use product development , 2002, CHI 2002.

[41]  Huiru Zheng,et al.  Developing and testing a telerehabilitation system for people following stroke: issues of usability , 2010 .