Rehabilitation professionals’ perceptions of the use of new visualisation software tools with people with stroke

References

• Durward B, Baer G, Rowe P. Functional human movement: measurement and analysis. London: Butterworth Heinemann; 1997.
   Google Scholar
• Macdonald AS, Loudon D, Docherty C. Innovation in envisioning dynamic biomechanical data to inform healthcare and design guidelines and strategy. NDA Research Programme: University of Sheffield 2009; [cited 2015 May 12]. Available from: http://www.newdynamics.group.shef.ac.uk/nda-findings-1.html.
   Google Scholar
• Craig P, Dieppe P, Macintyre S, et al. Developing and evaluating complex interventions: new guidance. London: Medical Research Council; 2008.
   Google Scholar
• Loudon D, Macdonald AS, Carse B, et al. Developing visualisation software for rehabilitation: investigating the requirements of patients, therapists and the rehabilitation process. Health Informatics J. 2012;18:171–180.
   PubMed Web of Science ®Google Scholar
• De Assis GA, Corrêa AGD, Martins MBR, et al. An augmented reality system for upper-limb post-stroke motor rehabilitation: a feasibility study. Disabil Rehabil Assist Technol. 2014;4:1–8.
   Google Scholar
• Green D, Wilson PH. Use of virtual reality in rehabilitation of movement in children with hemiplegia. Disabil Rehabil. 2012;34:593–604.
   PubMed Web of Science ®Google Scholar
• Mirelman A, Bonato P, Deutsch JE. Effects of training with a robot-virtual reality system compared with a robot along on the gait of individuals after stroke. Stroke. 2009;40;169–174.
   PubMed Web of Science ®Google Scholar
• Sampson M, Shau Y-W, King MJ. Bilateral upper limb trainer with virtual reality for post-stroke rehabilitation: case series report. Disabil Rehabil Assist Technol. 2012;7:55–62.
   PubMedGoogle Scholar
• Yang Y-R, Tsai M-P, Chuang T-Y, et al. Virtual-reality based training improves community ambulation in individuals with stroke: a randomized controlled trial. Gait Posture. 2008;28:201–206.
   PubMed Web of Science ®Google Scholar
• World Health Organisation. International classification of functioning, disability and health. Geneva: World Health Organisation; 2001.
   Google Scholar
• Lohse KR, Hilderman GE, Cheung KL, et al. Virtual reality therapy for adults post-stroke: a systematic review and meta-analysis exploring virtual environments and commercial games in therapy. PLoS One. 2014;9;e93318.
   PubMed Web of Science ®Google Scholar
• Rosewilliam S, Roskell CA, Pandyan AD. A systematic review and synthesis of the quantitative and qualitative evidence behind patient-centred goal setting in stroke rehabilitation. Clin Rehabil. 2011;25:501–514.
   PubMed Web of Science ®Google Scholar
• Nicholson SL, Donaghy M, Johnston M, et al. A qualitative theory guided analysis of stroke survivors’ perceived barriers and facilitators to physical activity. Disabil Rehabil. 2014;36:1857–1868.
   PubMed Web of Science ®Google Scholar
• Levack WMM, Dean SG, Siegert RJ, et al. Navigating patient-centred goal setting in inpatient stroke rehabilitation: how clinicians control the process to meet perceived professional responsibilities. Patient Educ Couns. 2011;85:206–213.
   PubMed Web of Science ®Google Scholar
• Drabble SJ, O’Cathain A, Thomas, et al. Describing qualitative research undertaken with randomized controlled trials in grant proposals: a documentary analysis. BMC Med Res Methodol. 2014;14:1–7.
   PubMed Web of Science ®Google Scholar
• O'Cathain A, Thomas KJ, Drabble SJ, et al. What can qualitative research do for randomised controlled trials? A systematic mapping review. BMJ Open. 2013;3:e002889.
   PubMed Web of Science ®Google Scholar
• Mawson S, Nasr N, Parker J, et al. Developing a personalized self-management system for post stroke rehabilitation; utilizing a user-centred design methodology. Disabil Rehabil. 2014;9:521–528.
   Google Scholar
• Parker J, Mawson S, Mountain G, et al. The provision of feedback through computer-based technology to promote self-managed post-stroke rehabilitation in the home. Disabil Rehabil Assist Technol. 2014;9:529–538.
   PubMedGoogle Scholar
• Lindqvist E, Borell L. Computer-based assistive technology and changes in daily living after stroke. Disabil Rehabil Assist Technol. 2012;7:364–371.
   PubMedGoogle Scholar
• May CR, Mair F, Finch T, et al. Development of a theory of implementation and integration: normalization process theory. Implementation Sci. 2009;4:29.
   PubMed Web of Science ®Google Scholar
• May C, Finch T. Implementing, embedding, and integrating practices: an outline of normalization process theory. Sociology. 2009;43:535–554.
   Google Scholar
• May C, Murray E, Finch T, et al. Normalization process theory on-line users’ manual and toolkit 2010; [cited 2015 Aug 21]. Available from: http://www.normalizationprocess.org
   Google Scholar
• Murray E, Treweek S, Pope C, et al. Normalisation process theory: a framework for developing, evaluating and implementing complex interventions. BMC Med. 2010;8:63.
   PubMed Web of Science ®Google Scholar
• Ballinger C. Writing up rigour: representing and evaluating good scholarship in qualitative research. Br J Occup Ther. 2004;67:540–546.
   Google Scholar
• Burns Cunningham K. Social research design: framework for integrating philosophical and practical elements. Nurse Res. 2014;22:32–37.
   PubMedGoogle Scholar
• Mason J. Qualitative researching. 2nd ed. London: Sage Publications; 2002.
   Google Scholar
• Morgan DL. Focus groups as qualitative research. London: Sage; 1997.
   Google Scholar
• Richie J, Spencer L. Qualitative data analysis for applied policy research. In: Bryman A, Burgess RG, editors. Analysing qualitative data. London: Routledge; 1994. p 173–194.
   Google Scholar
• Pollock A, St George B, Fenton M, et al. Top 10 research priorities relating to life after stroke-consensus from stroke survivors, caregivers and health care professionals. Int J Stroke. 2014;9:313–320.
   PubMed Web of Science ®Google Scholar
• National Clinical Guideline Centre. Stroke rehabilitation long term rehabilitation after stroke clinical guideline 162. London: National Institute for Health and Care Excellence; 2013.
   Google Scholar
• Scottish Intercollegiate Guidelines Network. Management of patients with stroke: rehabilitation, prevention and management of complications, and discharge planning a national clinical guideline no 118. 2010.
   Google Scholar
• Alt Murphy M, Resteghini C, Feys P, et al. An overview of systematic reviews on upper extremity outcome measures after stroke. BMC Neurol. 2015;15:29.
   PubMed Web of Science ®Google Scholar
• Salter K, Campbell N, Richardson M, et al. Outcome measures in stroke rehabilitation. In: Teasell R, Richardson M, Allen L, et al. editors. Evidence-based review of stroke rehabilitation. 2013; [cited on 2015 Aug 21]. Available from: www.ebrsr. com/evidence-review/21-outcome-measures.
   Google Scholar
• Brooks C, Ballinger C, Nutbeam D, et al. Literacy levels required to understand regularly accessed falls prevention websites aimed at the public. J Phys Ther Health Promot. 2013;1:8–14.
   Google Scholar
• Sallinen M, Hentonen O, Kärki A. Technology and active agency of older adults living in service house technology. Disabil Rehabil Assist Technol. 2015;10:27–31.
   PubMed Web of Science ®Google Scholar
• Moore G, Audrey S, Barker M, et al. Process evaluation of complex intervention UK Medical Research Council (MRC) guidance. London: MRC Population Health Science Research Network; 2014.
   Google Scholar
• May CR, Harrison R, Finch T, et al. Understanding the normalization of telemedicine services through qualitative evaluation. J Am Med Inform Assoc. 2003;10:596–604.
   PubMed Web of Science ®Google Scholar
• Pope C, Halford S, Turnbull J, et al. Using computer decision support systems in NHS emergency and urgent care: ethnographic study using normalisation process theory. BMC Health Serv Res. 2013;13:111.
   PubMed Web of Science ®Google Scholar