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BMC Neurology
Published in: BMC Neurology 1/2021

Open Access 01-12-2021 | Research article

Stakeholder consensus for decision making in eye-gaze control technology for children, adolescents and adults with cerebral palsy service provision: findings from a Delphi study

Authors: Petra Karlsson, Tom Griffiths, Michael T. Clarke, Elegast Monbaliu, Kate Himmelmann, Saranda Bekteshi, Abigail Allsop, René Pereksles, Claire Galea, Margaret Wallen

Published in: BMC Neurology | Issue 1/2021

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Abstract

Background

Limited research exists to guide clinical decisions about trialling, selecting, implementing and evaluating eye-gaze control technology. This paper reports on the outcomes of a Delphi study that was conducted to build international stakeholder consensus to inform decision making about trialling and implementing eye-gaze control technology with people with cerebral palsy.

Methods

A three-round online Delphi survey was conducted. In Round 1, 126 stakeholders responded to questions identified through an international stakeholder Advisory Panel and systematic reviews. In Round 2, 63 respondents rated the importance of 200 statements generated by in Round 1. In Round 3, 41 respondents rated the importance of the 105 highest ranked statements retained from Round 2.

Results

Stakeholders achieved consensus on 94 of the original 200 statements. These statements related to person factors, support networks, the environment, and technical aspects to consider during assessment, trial, implementation and follow-up. Findings reinforced the importance of an individualised approach and that information gathered from the user, their support network and professionals are central when measuring outcomes. Information required to support an application for funding was obtained.

Conclusion

This Delphi study has identified issues which are unique to eye-gaze control technology and will enhance its implementation with people with cerebral palsy.
Appendix
Available only for authorised users
Literature
1.
Himmelmann K, Hagberg G, Wiklund L, Eek MN, Uvebrant P. Dyskinetic cerebral palsy: a population-based study of children born between 1991 and 1998. Dev Med Child Neurol. 2007;49(4):246–51.CrossRef
2.
Nordberg A, Miniscalco C, Lohmander A, et al. Speech problems affect more than one in two children with cerebral palsy: Swedish population-based study. Acta Paed. 2013;102(2):161–6.CrossRef
3.
4.
Myrden A, Schudlo L, Weyand S, et al. Trends in communicative access solutions for children with cerebral palsy. J Child Neurol. 2014;29(8):1108–18.CrossRef
5.
Holmqvist E, Thunberg G, Peny DM. Gaze-controlled communication technology for children with severe multiple disabilities: parents and professionals’ perception of gains, obstacles, and prerequisites. Assist Technol. 2018;30(4):201–8.CrossRef
6.
Borgestig M, Sandqvist J, Parsons R, et al. Eye gaze performance for children with severe physical impairments using gaze-based assistive technology: a longitudinal study. Assist Technol. 2016;28(2):93–102.CrossRef
7.
Perfect E, Hoskin E, Noyek S, et al. A systematic review investigating outcome measures and uptake barriers when children and youth with complex disabilities use eye gaze assistive technology. Dev Neurorehabilit. 2019:1–15.
8.
Van Niekerk K, Tönsing K. Eye gaze technology: a south African perspective. Disabil Rehabil Assist Technol. 2015;10(4):340–6.CrossRef
9.
Karlsson P, Wallen M. Parent perception of two eye-gaze control technology systems in young children with cerebral palsy: pilot study. Stud Health Technol Inform. 2017;242:1095–102.PubMed
10.
Bekteshi S, Konings M, Vanmechelen I, Deklerck J, Ortibus E, Aerts J-M, et al. Eye gaze gaming intervention in children with Dyskinetic cerebral palsy: a pilot study of task performance and its relation with dystonia and Choreoathetosis. Dev Neurorehabilit. 2020:1–9.
11.
Borgestig M, Sandqvist J, Ahlsten G, et al. Gaze-based assistive technology in daily activities in children with severe physical impairments: an intervention study. Dev Neurorehabilit. 2016:1–13.
12.
Hornof AJ, Cavender A, editors. EyeDraw: Enabling children with severe motor impairments to draw with their eyes. Proceedings of the SIGCHI conference on Human factors in computing systems; 2005: ACM.
13.
Karlsson P, Bech A, Stone H, et al. Eyes on communication: Trialling eye-gaze control technology in young children with dyskinetic cerebral palsy. Dev Neurorehabilit. 2019;22(2):134–40. 
14.
Man DW, Wong M-SL. Evaluation of computer-access solutions for students with quadriplegic athetoid cerebral palsy. Am J Occup Ther. 2007;61(3):355–64.CrossRef
15.
Vickers S, Istance H, Hyrskykari A. Performing locomotion tasks in immersive computer games with an adapted eye-tracking interface. ACM Trans Accessible Comput (TACCESS). 2013;5(1):2.
16.
Najafi L, Friday M, Robertson Z. Two case studies describing assessment and provision of eye gaze technology for people with severe physical disabilities. J Assist Technol. 2008;2(2):6–12.CrossRef
17.
Clarke M, Wright J, Griffiths T, et al. A proposed framework for decision-making for assistive communication technology support: many perspectives, but one common goal. J Assist Technol. 2011.
18.
Wilkinson KM, Mitchell T. Eye tracking research to answer questions about augmentative and alternative communication assessment and intervention. Augment Alternat Commun. 2014;30(2):106–19.CrossRef
19.
de Witte L, Steel E, Gupta S, et al. Assistive technology provision: towards an international framework for assuring availability and accessibility of affordable high-quality assistive technology. Disabil Rehabil Assist Technol. 2018;13(5):467–72.CrossRef
20.
Light J, McNaughton D. Putting people first: re-thinking the role of technology in augmentative and alternative communication intervention. Augment Alternat Commun. 2013;29(4):299–309.CrossRef
21.
Mandak K, O’Neill T, Light J, et al. Bridging the gap from values to actions: a family systems framework for family-centered AAC services. Augment Alternat Commun. 2017;33(1):32–41.
22.
Karlsson P, Allsop A, Dee-Price BJ, et al. Eye-gaze control technology for children, adolescents and adults with cerebral palsy with significant physical disability: findings from a systematic review. Dev Neurorehabil. 2017;1:1–9.
23.
Rytterström P, Borgestig M, Hemmingsson H. Teachers’ experiences of using eye gaze-controlled computers for pupils with severe motor impairments and without speech. Eur J Spec Needs Educ. 2016:1–14.
24.
Borgestig M, Rytterström P, Hemmingsson H. Gaze-based assistive technology used in daily life by children with severe physical impairments: parents’ experiences. Dev Neurorehabil. 2017;20(5):301–8.
25.
Sackett DL, Rosenberg WM, Gray JM, et al. Evidence based medicine: what it is and what it isn't; 1996. p. 71–72.
26.
Jünger S, Payne SA, Brine J, et al. Guidance on conducting and REporting DElphi studies (CREDES) in palliative care: recommendations based on a methodological systematic review. Palliat Med. 2017;31(8):684–706.CrossRef
27.
Williams PL, Webb C. The Delphi technique: a methodological discussion. J Adv Nurs. 1994;19(1):180–6.CrossRef
28.
Keeney S, Hasson F, McKenna HP. A critical review of the Delphi technique as a research methodology for nursing. Int J Nurs Stud. 2001;38(2):195–200.CrossRef
29.
Hasson F, Keeney S, McKenna H. Research guidelines for the Delphi survey technique. J Adv Nurs. 2000;32(4):1008–15.PubMed
30.
Grant S, Hazlewood GS, Peay HL, et al. Practical considerations for using online methods to engage patients in guideline development. Patient Centered Outcomes Res. 2017:1–12.
31.
Izaryk K, Skarakis-Doyle E. Using the Delphi technique to explore complex concepts in speech-language pathology: an illustrative example from children's social communication. Am J Speech-Lang Pathol. 2017;26(4):1225–35.CrossRef
32.
Toronto C. Considerations when conducting e-Delphi research: a case study. Nurs Res. 2017;25(1):10–5.CrossRef
33.
Staniszewska S, Brett J, Simera I, et al. GRIPP2 reporting checklists: tools to improve reporting of patient and public involvement in research. Res Involv Engagem. 2017;3(1):13.CrossRef
34.
Kearney A, Williamson P, Young B, et al. Priorities for methodological research on patient and public involvement in clinical trials: a modified Delphi process. Health Expect. 2017;20(6):1401–10.CrossRef
35.
Braun V, Clarke V. Using thematic analysis in psychology. Qual Res in Psychol. 2006;3(2):77–101.CrossRef
36.
SPSS v.25. Statistical Package Social Science, SPSS for Windows; 2018.
37.
Palisano RJ, Rosenbaum P, Bartlett D, et al. Content validity of the expanded and revised gross motor function classification system. Dev Med Child Neurol. 2008;50(10):744–50.
38.
Eliasson A-C, Krumlinde-Sundholm L, Rösblad B, et al. The manual ability classification system (MACS) for children with cerebral palsy: scale development and evidence of validity and reliability. Dev Med Child Neurol. 2006;48(07):549–54.
39.
Hidecker MJC, Paneth N, Rosenbaum PL, et al. Developing and validating the communication function classification system for individuals with cerebral palsy. Dev Med Child Neurol. 2011;53(8):704–10.
40.
Pennington L, Virella D, Mjøen T, da Graça Andrada M, Murray J, Colver A, Himmelmann K, Rackauskaite G, Greitane A, Prasauskiene A, Andersen G. Development of The Viking Speech Scale to classify the speech of children with cerebral palsy. Res Dev Disabil 2013;34(10):3202-10.
41.
Kent-Walsh J, Murza KA, Malani MD, et al. Effects of communication partner instruction on the communication of individuals using AAC: a meta-analysis. Augment Alternat Commun. 2015;31(4):271–84.
42.
Bailey RL, Parette HP Jr, Stoner JB, et al. Family members’ perceptions of augmentative and alternative communication device use. Lang Speech Hear Serv Sch. 2006;37(1):50–60.
43.
de Jonge D, Layton N, Vicary F, et al. Motivations and incentives: Exploring assistive technology service delivery from the perspectives of multiple stakeholders. In: Proceedings of New Frontiers in Assistive Technol Conf (RESNA 2015): Univ South Qld; 2015.
44.
Delacy MJ, Reid SM, Group ACPR. Profile of associated impairments at age 5 years in Australia by cerebral palsy subtype and gross motor function classification system level for birth years 1996 to 2005. Dev Med Child Neurol. 2016;58:50–6.
45.
Deramore Denver B, Froude E, Rosenbaum P, Wilkes-Gillan S, Imms C. Measurement of visual ability in children with cerebral palsy: a systematic review. Devl Med Child Neurol. 2016;58(10):1016–29.
46.
Colenbrander A. Assessment of functional vision and its rehabilitation. Acta Ophthalmol. 2010;88(2):163–73.
47.
Dufresne D, Dagenais L, Shevell MI, et al. Spectrum of visual disorders in a population-based cerebral palsy cohort. Pediatr Neurol. 2014;50(4):324–8.
48.
Deramore Denver B, Adolfsson M, Froude E, Rosenbaum P, Imms C. Methods for conceptualising ‘visual ability’as a measurable construct in children with cerebral palsy. BMC Med Res Methodol. 2017;17(1):46.
49.
Baranello G, Signorini S, Tinelli F, Guzzetta A, Pagliano E, Rossi A, et al. Visual function classification system for children with cerebral palsy: development and validation. Dev Med Child Neurol. 2020;62(1):104–10.
50.
Clarke M, Cooper R, Aberbach G, Woghiren A, Sargent J, Griffiths T, et al. Eye-pointing classification in non-speaking children with severe cerebral palsy. 2019. Available from: http://​www.​ucl.​ac.​uk/​gaze
51.
Lund SK, Light J. Long-term outcomes for individuals who use augmentative and alternative communication: part III–contributing factors. Augment Alternat Commun. 2007;23(4):323–35.
52.
Boise L, White D. The family's role in person-centered care: practice considerations. J Psychosoc Nurs Ment Health Serv. 2004;42(5):12–20.
53.
Cook AM, Polgar JM. Cook and Hussey’s assistive technologies-E-book: principles and practice: Elsevier Health Sciences; 2013.
54.
Kent-Walsh J, Mcnaughton D. Communication partner instruction in AAC: present practices and future directions. Augment Alternat Commun. 2005;21(3):195–204.
55.
Binger C, Ball L, Dietz A, et al. Personnel roles in the AAC assessment process. Augment Alternat Commun. 2012;28(4):278–88.
56.
Enderby P. Introducing the therapy outcome measure for AAC services in the context of a review of other measures. Disabil Rehabil Assist Technol. 2014;9(1):33–40.
57.
Soto G, Mu Ller E, Hunt P, et al. Professional skills for serving students who use AAC in general education classrooms: a team perspective. Lang Speech Hear Serv Sch. 2001;32(1):51–6.
58.
Andrich R, Mathiassen N-E, Hoogerwerf E-J, et al. Service delivery systems for assistive technology in Europe: an AAATE/EASTIN position paper. Technol Disabil. 2013;25(3):127–46.
59.
Zabala J. The SETT Framework: critical areas to consider when making informed assistive technology decisions. 1995.
60.
Desmond D, Layton N, Bentley J, et al. Assistive technology and people: a position paper from the first global research, innovation and education on assistive technology (GREAT) summit. Disabil Rehabil Assist Technol. 2018;13(5):437–44.
61.
Kiresuk TJ, Smith A, Cardillo JE. Goal attainment scaling: applications, theory, and measurement: Psychol Press; 2014.
62.
Ryan SE, Renzoni AM. Family Impact Scale of Assistive Technology Scale for AAC (FIATS-AAC). 2010. [Measurement instrument].
63.
Murphy BR, Boa S, Enderby P. Testing the reliability and validity of the therapy outcome measure for AAC. Scotland: NHS education for Scotland; 2014. [Measurement instrument].
64.
Wallace SE. AAC use by people with TBI: affects of cognitive impairments. Perspect Augment Alternat Commun. 2010;19(3):79–86.
65.
Nulty DD. The adequacy of response rates to online and paper surveys: what can be done? Ass Eval in Higher Educ. 2008;33(3):301–14.
Metadata
Title
Stakeholder consensus for decision making in eye-gaze control technology for children, adolescents and adults with cerebral palsy service provision: findings from a Delphi study
Authors
Petra Karlsson
Tom Griffiths
Michael T. Clarke
Elegast Monbaliu
Kate Himmelmann
Saranda Bekteshi
Abigail Allsop
René Pereksles
Claire Galea
Margaret Wallen
Publication date
01-12-2021
Publisher
BioMed Central
Published in
BMC Neurology / Issue 1/2021
Electronic ISSN: 1471-2377
DOI
https://doi.org/10.1186/s12883-021-02077-z

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