Hostname: page-component-745bb68f8f-lrblm Total loading time: 0 Render date: 2025-01-13T12:56:41.478Z Has data issue: false hasContentIssue false
  • English
  • Français

Clinician experiences with using assistive technology in brain injury rehabilitation: a survey of clinician capability, attitudes, and barriers

Published online by Cambridge University Press:  23 March 2023

Kavya Pilli ,
Brendan Worne  and
Grahame Simpson Open the ORCID record for Grahame Simpson [Opens in a new window]
Kavya Pilli*
Affiliation:
Liverpool Brain Injury Unit, Liverpool Hospital, Sydney, Australia
Brendan Worne
Affiliation:
Brain Injury Rehabilitation Research Group, Ingham Institute for Applied Medical Research, Sydney, Australia
Grahame Simpson
Affiliation:
Brain Injury Rehabilitation Research Group, Ingham Institute for Applied Medical Research, Sydney, Australia John Walsh Centre of Rehabilitation Research, Kolling Institute, Sydney, Australia Faculty of Medicine and Health, University of Sydney, Sydney, Australia
*
*Corresponding author. Email: kavya.pilli@health.nsw.gov.au
Get access

Abstract

Background:

The rise in assistive technology (AT) solutions to support people with an acquired brain injury (ABI) has warranted clinicians to build capability in assisting clients to select goal-centred AT. The study explored, amongst ABI clinicians, (a) capability, attitudes, and barriers with AT implementation, (b) age-related differences in technology self-efficacy and capability (c) strategies to support AT use in rehabilitation and (d) thematic analysis of AT-related experiences.

Method:

Mixed methods design. Online survey circulated to ABI clinicians across New South Wales, Australia, comprising purpose-designed items as well as the Modified Computer Self-Efficacy Scale (MCSES; range 0–100)

Results:

Clinicians (n = 123) were evenly distributed across decadal age groups. The majority were female (90%, n = 111) and one-third were occupational therapists.

Clinicians scored strongly on the MCSES (Mdn = 76, IQR = 19), with younger age groups significantly associated with higher scores (H[3] = 9.667, p = .022). Most clinicians (92%) were knowledgeable of mainstream technology for personal use, but over half (65%) reported insufficient knowledge of suitable AT for clients. Clinicians reported positive attitudes towards AT, however, time to research and develop proficiency with a range of AT was the primary barrier (81%).

Thematic analysis suggested that whilst the ideal AT experience is client-motivated requiring multidisciplinary guidance, the clinician role and experience with AT is evolving, influenced by rapid technological advancement and extrinsic opportunities to access AT.

Conclusions:

Whilst clinicians have positive attitudes towards AT, there is a gap in clinician implementation. There is need to support further resources to build clinician capability and access to AT.

Keywords

Acquired brain injurytraumatic brain injuryassistive technologycliniciansself-efficacytechnology acceptancerehabilitationbehaviour change
Type
Original Article
Information
Brain Impairment , Volume 24 , Issue 2 , September 2023 , pp. 185 - 203
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Australasian Society for the Study of Brain Impairment

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alashram, A. R., Annino, G., Padua, E., Romagnoli, C., & Mercuri, N. B. (2019). Cognitive rehabilitation post traumatic brain injury: A systematic review for emerging use of virtual reality technology. Journal of Clinical Neuroscience, 66, 209–219. doi: 10.1016/j.jocn.2019.04.026 CrossRefGoogle ScholarPubMed
Andrew, N. E., Kilkenny, M., Naylor, R., Purvis, T., Lalor, E., Moloczij, N., & Cadilhac, D. A. (2014). Understanding long-term unmet needs in Australian survivors of stroke. International Journal of Stroke, 9, 106–112.CrossRefGoogle ScholarPubMed
Atkins, L., Francis, J., Islam, R., O’Connor, D., Patey, A., Ivers, N., …, Michie, S. (2017). A guide to using the Theoretical Domains Framework of behaviour change to investigate implementation problems. Implementation Science, 12(1), 1–18.CrossRefGoogle ScholarPubMed
Australian Institute of Health and Welfare (2007). Disability in Australia: Acquired brain injury. Canberra: AIHW.Google Scholar
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.CrossRefGoogle Scholar
Brunner, M., Hemsley, B., Togher, L., & Palmer, S. (2017). Technology and its role in rehabilitation for people with cognitive-communication disability following a traumatic brain injury (TBI). Brain Injury, 31(8), 1028–1043.CrossRefGoogle ScholarPubMed
Charters, E., Gillett, L., & Simpson, G. K. (2015). Efficacy of electronic portable assistive devices for people with acquired brain injury: A systematic review. Neuropsychological Rehabilitation, 25(1), 82–121.CrossRefGoogle ScholarPubMed
Chen, C. C., & Bode, R. K. (2011). Factors influencing therapists’ decision-making in the acceptance of new technology devices in stroke rehabilitation. American Journal of Physical Medicine & Rehabilitation, 90(5), 415–425.CrossRefGoogle ScholarPubMed
Cohen, J. (1992). Statistical power analysis. Current Directions in Psychological Science, 1(3), 98–101.CrossRefGoogle Scholar
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189–211.CrossRefGoogle Scholar
Culler, K. H., Wang, Y. C., Byers, K., & Trierweiler, R. (2011). Barriers and facilitators of return to work for individuals with strokes: Perspectives of the stroke survivor, vocational specialist, and employer. Topics in Stroke Rehabilitation, 18(4), 325–340.CrossRefGoogle ScholarPubMed
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.CrossRefGoogle Scholar
de Joode, E., van Heugten, C., Verhey, F., & van Boxtel, M. (2010). Efficacy and usability of assistive technology for patients with cognitive deficits: A systematic review. Clinical Rehabilitation, 24(8), 701–714.CrossRefGoogle ScholarPubMed
de Joode, E. A., van Boxtel, M. P., Verhey, F. R., & van Heugten, C. M. (2012). Use of assistive technology in cognitive rehabilitation: Exploratory studies of the opinions and expectations of healthcare professionals and potential users. Brain Injury, 26(10), 1257–1266.CrossRefGoogle ScholarPubMed
Downing, M., Bragge, P., & Ponsford, J. (2019). Cognitive rehabilitation following traumatic brain injury: A survey of current practice in Australia. Brain Impairment, 20(1), 24–36.CrossRefGoogle Scholar
Gagnon-Roy, M., Bier, N., Couture, M., Giroux, S., Pigot, H., Zarshenas, S., & Bottari, C. (2021). Facilitators and obstacles to the use of a cognitive orthosis for meal preparation within the homes of adults with a moderate to severe traumatic brain injury: Informal caregivers and health-care professionals’ perspectives. Assistive Technology, 34(3), 281–288.CrossRefGoogle Scholar
Gillespie, A., Best, C., & O’Neill, B. (2012). Cognitive function and assistive technology for cognition: A systematic review. Journal of the International Neuropsychological Society, 18(1), 1–19.CrossRefGoogle ScholarPubMed
Hamilton, C., Lovarini, M., McCluskey, A., Folly de Campos, T., & Hassett, L. (2019). Experiences of therapists using feedback-based technology to improve physical function in rehabilitation settings: A qualitative systematic review. Disability and Rehabilitation, 41(15), 1739–1750.CrossRefGoogle ScholarPubMed
Hart, T., O'Neil-Pirozzi, T., & Morita, C. (2003). Clinician expectations for portable electronic devices as cognitive-behavioural orthoses in traumatic brain injury rehabilitation. Brain Injury, 17(5), 401–411.CrossRefGoogle ScholarPubMed
Hassett, L., van den Berg, M., Lindley, R. I., Crotty, M., McCluskey, A., van der Ploeg, H. P., …Sherrington, C. (2020). Digitally enabled aged care and neurological rehabilitation to enhance outcomes with Activity and MObility UsiNg Technology (AMOUNT) in Australia: A randomised controlled trial. PLoS Medicine, 17(2), e1003029.CrossRefGoogle Scholar
Hewson, C., Buchanan, T., Brown, I., Coulson, N. S., Hagger-Johnson, G., Joinson, A., & Oates, J. (2021). Ethics guidelines for internet-mediated research. London: British Psychological Society.Google Scholar
Ienca, M., Fabrice, J., Elger, B., Caon, M., Scoccia Pappagallo, A., Kressig, R. W., & Wangmo, T. (2017). Intelligent assistive technology for Alzheimer’s disease and other dementias: A systematic review. Journal of Alzheimer’s Disease, 56(4), 1301–1340.CrossRefGoogle ScholarPubMed
Jamwal, R., Callaway, L., Ackerl, J., Farnworth, L., & Winkler, D. (2017). Electronic assistive technology used by people with acquired brain injury in shared supported accommodation: Implications for occupational therapy. British Journal of Occupational Therapy, 80(2), 89–98.CrossRefGoogle Scholar
Juengst, S. B., Graham, K. M., Pulantara, I. W., McCue, M., Whyte, E. M., Dicianno, B. E., ... & Wagner, A. K. (2015). Pilot feasibility of an mHealth system for conducting ecological momentary assessment of mood-related symptoms following traumatic brain injury. Brain Injury, 29(11), 1351–1361.CrossRefGoogle ScholarPubMed
Karlsson, P., Johnston, C., & Barker, K. (2018). Influences on students’ assistive technology use at school: The views of classroom teachers, allied health professionals, students with cerebral palsy and their parents. Disability and Rehabilitation: Assistive Technology, 13(8), 763–771.Google ScholarPubMed
Kelly, M., McDonald, S., & Frith, M. H. (2017). Assessment and rehabilitation of social cognition impairment after brain injury: Surveying practices of clinicians. Brain Impairment, 18(1), 11–35.CrossRefGoogle Scholar
Laver, K., George, S., Ratcliffe, J., & Crotty, M. (2012). Measuring technology self-efficacy: Reliability and construct validity of a modified computer self-efficacy scale in a clinical rehabilitation setting. Disability and Rehabilitation, 34(3), 220–227.CrossRefGoogle Scholar
Leopold, A., Louri, A., Petras, H., & Elias, E. (2015). The use of assistive technology for cognition to support the performance of daily activities for individuals with cognitive disabilities due to traumatic brain injury: The current state of research. NeuroRehabilitation, 37(3), 359–378.CrossRefGoogle Scholar
Lloréns, R., Noé, E., Colomer, C., & Alcañiz, M. (2015). Effectiveness, usability, and cost-benefit of a virtual reality–based telerehabilitation program for balance recovery after stroke: A randomized controlled trial. Archives of Physical Medicine and Rehabilitation, 96(3), 418–425.CrossRefGoogle ScholarPubMed
Michie, S., Atkins, L., & West, R. (2014). The behaviour change wheel. A guide to designing interventions (1st ed., pp. 1003–1010). Sutton: Silverback Publishing.Google Scholar
National Health and Medical Research Council. (2014). Ethical considerations in quality assurance and evaluation activities.Google Scholar
Norup, A., Kruse, M., Soendergaard, P. L., Rasmussen, K. W., & Biering-Sørensen, F. (2020). Socioeconomic consequences of traumatic brain injury: A Danish nationwide register-based study. Journal of Neurotrauma, 37(24), 2694–2702.CrossRefGoogle ScholarPubMed
O’Neil-Pirozzi, T. M., Kendrick, H., Goldstein, R., & Glenn, M. (2004). Clinician influences on use of portable electronic memory devices in traumatic brain injury rehabilitation. Brain Injury, 18(2), 179–189.CrossRefGoogle ScholarPubMed
Oyesanya, T. O., Thompson, N., Arulselvam, K., & Seel, R. T. (2021). Technology and TBI: Perspectives of persons with TBI and their family caregivers on technology solutions to address health, wellness, and safety concerns. Assistive Technology, 33(4), 190–200.CrossRefGoogle ScholarPubMed
Plackett, R., Thomas, S., & Thomas, S. (2017). Professionals’ views on the use of smartphone technology to support children and adolescents with memory impairment due to acquired brain injury. Disability and Rehabilitation: Assistive Technology, 12(3), 236–243.Google ScholarPubMed
Ponsford, J., Sloan, S., & Snow, P. (2013). Traumatic brain injury: Rehabilitation for everyday adaptive living (2nd ed.). New York: Psychology Press.Google Scholar
Sabaz, M., Simpson, G. K., Walker, A. J., Rogers, J. M., Gillis, I., & Strettles, B. (2014). Prevalence, comorbidities, and correlates of challenging behavior among community-dwelling adults with severe traumatic brain injury: A multicenter study. The Journal of Head Trauma Rehabilitation, 29(2), E19–E30.CrossRefGoogle ScholarPubMed
Simpson, G. K., McRae, P., Hallab, L., Daher, M., & Strettles, B. (2020). Participation in competitive employment after severe traumatic brain injury: New employment versus return to previous (pre-injury) employment. Neuropsychological Rehabilitation, 30(6), 995–1012.CrossRefGoogle ScholarPubMed
Sloan, S., Callaway, L., & Winkler, D. (2009). Changes in care and support needs following community-based intervention for individuals with acquired brain injury. Brain Impairment, 10(3), 295–306.CrossRefGoogle Scholar
Steel, E. J., Layton, N. A., Foster, M. M., & Bennett, S. (2016). Challenges of user-centred assistive technology provision in Australia: Shopping without a prescription. Disability and Rehabilitation: Assistive Technology, 11(3), 235–240.Google ScholarPubMed
Tate, R. L., Lane-Brown, A. T., Myles, B. M., & Cameron, I. D. (2020). A longitudinal study of support needs after severe traumatic brain injury. Brain Injury, 34(8), 991–1000.CrossRefGoogle ScholarPubMed
Thompson, H. S., & Ryan, A. (2009). The impact of stroke consequences on spousal relationships from the perspective of the person with stroke. Journal of Clinical Nursing, 18(12), 1803–1811.CrossRefGoogle ScholarPubMed
Vaezipour, A., Whelan, B. M., Wall, K., & Theodoros, D. (2019). Acceptance of rehabilitation technology in adults with moderate to severe traumatic brain injury, their caregivers, and healthcare professionals: A systematic review. The Journal of Head Trauma Rehabilitation, 34(4), E67–E82.CrossRefGoogle ScholarPubMed
Wong, D., Sinclair, K., Seabrook, E., Mckay, A., & Ponsford, J. (2017). Smartphones as assistive technology following traumatic brain injury: A preliminary study of what helps and what hinders. Disability and Rehabilitation, 39(23), 2387–2394.CrossRefGoogle ScholarPubMed
World Health Organization (2017). Global priority research agenda for improving access to high-quality affordable assistive technology. World Health Organization.Google Scholar
World Health Organization (2021). Assistive technology. Retrieved from https://www.who.int/teams/health-product-policy-and-standards/assistive-and-medical-technology/assistive-technologyhttps://www.who.int/news-room/fact-sheets/detail/assistive-technology Google Scholar
Zarshenas, S., Gagnon-Roy, M., Couture, M., Bier, N., Giroux, S., Nalder, E., …, Canadian Traumatic Brain Injury Research Consortium (2020). Potential of using an assistive technology to address meal preparation difficulties following acquired brain injury: Clients’ and caregivers’ perspectives. Disability and Rehabilitation: Assistive Technology, 1–9. doi: 10.1080/17483107.2020.1867244.Google Scholar
Supplementary material: File

Pilli et al. supplementary material

Table S1

Download Pilli et al. supplementary material(File)
File 15.1 KB