Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-27T23:14:50.187Z Has data issue: false hasContentIssue false
  • English
  • Français

Community Participation for People with Trauma Injuries: A Study Protocol of a Crossover Randomised Controlled Trial of the Effectiveness of a Community Mobility Group Intervention (CarFreeMe TI)

Published online by Cambridge University Press:  13 February 2019

Stacey George Open the ORCID record for Stacey George [Opens in a new window] ,
Christopher Barr ,
Angela Berndt ,
Maria Crotty ,
Rachel Milte ,
Amy Nussio  and
Jacki Liddle
Stacey George*
Affiliation:
Occupational Therapy/Clinical Rehabilitation, College of Nursing and Health Sciences, Flinders University, Adelaide, Australia
Christopher Barr
Affiliation:
Clinical Rehabilitation, College of Nursing and Health Sciences, Flinders University, Adelaide, Australia
Angela Berndt
Affiliation:
Occupational Therapy, University of South Australia, Adelaide, Australia
Maria Crotty
Affiliation:
Rehabilitation, Aged and Extended Care, College of Medicine and Public Health, Flinders University, Adelaide, Australia
Rachel Milte
Affiliation:
Institute for Choice, University of South Australia, Adelaide, Australia
Amy Nussio
Affiliation:
Occupational Therapy/Clinical Rehabilitation, College of Nursing and Health Sciences, Flinders University, Adelaide, Australia
Jacki Liddle
Affiliation:
School of Health and Rehabilitation Sciences and School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
*
Address for correspondence: Stacey George. College of Nursing and Health Sciences, Flinders University, GPO Box 2100, Adelaide, 5001, Australia E-mail: [email protected].
Get access

Abstract

Background: Following traumatic brain and spinal cord injuries, maximising community participation leads to better physical and mental health outcomes.

Objectives: To determine the effectiveness and health system resource use of a group intervention (CarFreeMe TI) on community participation in people with complex trauma injuries.

Method: Randomised crossover trial of 54 participants, recruited from rehabilitation services in Adelaide, Australia. Inclusion criteria is a trauma injury, unable to return to full driving, aged over 18 years of age, adequate cognition/behavioural/communication abilities to participate in sessions and mobile. Exclusion criterion is living in setting where alternative transport is provided. Participants will be randomly assigned on a 1:1 allocation basis, to receiving Phase 1 CarFreeMe TI-group-based intervention or Phase 2 information related to transport options. Then, crossover to Phase 1 or 2 will occur. Primary outcome measure is community participation using a Global Positioning System. Secondary outcome measures include Community Mobility Self-efficacy Scale; CarFreeMe TI Transport Questionnaire, AQOL, EQ-5D-5L; Carer's Community Mobility Self-efficacy Scale and Modified Carer Strain Index for carers of participants. Outcome assessors will be blinded to group allocation. All analyses will be on an intention to treat basis with difference in community participation between the groups determined via a GLM ANOVA and the significance between groups on other measures using independent sample t-tests. It is hypothesised that the community mobility intervention (CarFreeMeTI) will result in increased community participation.

Discussion: The results will provide proof of concept information on the feasibility and inform allocation of resources for people with complex trauma injuries.

Trial registration: Australian and New Zealand Clinical Trials Register (ANZCTR): ACTRN12616001254482.

Keywords

Trauma injuriestraumatic brain injuryspinal cord injuriesgroup-based interventioncommunity mobilityparticipationcommunity participation
Type
Protocols
Information
Brain Impairment , Volume 20 , Issue 1 , March 2019 , pp. 96 - 103
Copyright
Copyright © Australasian Society for the Study of Brain Impairment 2019 

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

Alali, A.S., Burton, K., Fowler, R.A., Naimark, D.M., Scales, D.C., Mainprize, T.G., & Nathens, A.B. (2015). Economic evaluations in the diagnosis and management of traumatic brain injury: A systematic review and analysis of quality. Value in Health, 18 (5), 721–734.Google Scholar
Barclay, L., McDonald, R., & Lentin, P. (2015). Social and community participation following spinal cord injury: A critical review. International Journal of Rehabilitation Research, 38 (1), 1–19.Google Scholar
Cairns, S., Harmer, C., Hopkin, J., & Skippon, S. (2014). Sociological perspectives on travel and mobilities: A review. Transportation Research Part A: Policy and Practice, 63 (5), 107–117.Google Scholar
Classen, S., Levy, C., McCarthy, D., Mann, W.C., Lanford, D., & Waid-Ebbs, J.K. (2009). Traumatic brain injury and driving assessment: An evidence-based literature review. American Journal of Occupational Therapy, 63 (5), 580–591.Google Scholar
Access Economics (2009). The economic cost of spinal cord injury and traumatic brain injury in Australia. Report by Access Economics for the Victorian Neurotrauma Initiative, vol. 31. Canberra: Access Economics.Google Scholar
Grimby, G. (2010). The importance of health economics in rehabilitation medicine. Journal of Rehabilitation Medicine, 42, 284–285.Google Scholar
Hawley, C.A. (2001). Return to driving after head injury. Journal of Neurology, Neurosurgery & Psychiatry, 70 (6), 761–766.Google Scholar
Hawthorne, G., Richardson, J., & Osborne, R. (1999). The assessment of quality of life (AQoL) instrument: A psychometric measure of health-related quality of life. Quality of Life Research, 8 (3), 209–224.Google Scholar
Herdman, M., Gudex, C., Lloyd, A., Janssen, M., Kind, P., Parkin, D. . . . Badia, X. (2011). Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research, 20 (10), 1727–1736.Google Scholar
Hordacre, B., Barr, C., & Crotty, M. (2014). Use of an activity monitor and GPS device to assess community activity and participation in transtibial amputees. Sensors, 14 (4), 5845–5859.Google Scholar
Juengst, S.B., Adams, L.M., Bogner, J.A., Arenth, P.M., O'Neil-Pirozzi, T.M., Dreer, L.E. . . . Wagner, A.K. (2015). Trajectories of life satisfaction after TBI: Influence of life roles, age, cognitive disability, and depressive symptoms. Rehabilitation Psychology, 60 (4), 353–364.Google Scholar
Liddle, J., Fleming, J., McKenna, K., Turpin, M., Whitelaw, P., & Allen, S. (2012). Adjustment to loss of the driving role following traumatic brain injury: A qualitative exploration with key stakeholders. Austratlian Occupational Therapy Journal, 59 (1), 79–88. doi: 10.1111/j.1440-1630.2011.00978.xGoogle Scholar
Liddle, J., Fleming, J., Mckenna, K., Turpin, M., Whitelaw, P., & Allen, S. (2011). Driving and driving cessation after traumatic brain injury: Processes and key times of need. Disability and Rehabilitation, 33 (25–26), 2574–2586.Google Scholar
Liddle, J., Hayes, R., Gustafsson, L., & Fleming, J. (2014a). Managing driving issues after an acquired brain injury: Strategies used by health professionals. Australian Occupational Therapy Journal, 61 (4), 215–223.Google Scholar
Liddle, J., Haynes, M., Pachana, N.A., Mitchell, G., McKenna, K., & Gustafsson, L. (2014b). Effect of a group intervention to promote older adults’ adjustment to driving cessation on community mobility: A randomized controlled trial. The Gerontologist, 54 (3), 409–422.Google Scholar
Liddle, J., Turpin, M., Carlson, G., & McKenna, K. (2008). The needs and experiences related to driving cessation for older people. British Journal of Occupational Therapy, 71 (9), 379–388.Google Scholar
Lorig, K., Stewart, A., Ritter, P., Gonzalez, V.M., Laurent, D., & Lynch, J. (1996). Outcome measures for health education and other health care interventions. California: Sage Publications.Google Scholar
McCrea, M., Iverson, G.L., McAllister, T.W., Hammeke, T.A., Powell, M.R., Barr, W.B., & Kelly, J.P. (2009). An integrated review of recovery after mild traumatic brain injury (MTBI): Implications for clinical management. The Clinical Neuropsychologist, 23 (8), 1368–1390.Google Scholar
Medical Services Advisory Committee (2016). Technical guidelines for preparing assessment reports for the Medical Services Advisory Committee – Medical service type: Therapeutic (Version 2.0). Canberra: Australian Government Department of Health.Google Scholar
National Institute for Health and Care Excellence (2013). Guide to the methods of technology appraisal 2013. London: National Institute for Health and Care Excellence.Google Scholar
Norweg, A. (2011). Patterns, predictors and associated benefits of driving a modified vehicle after spinal cord injury: Findings from the national spinal cord injury model systems. Archives of Physical Medicine & Rehabilitation, 92 (3), 477–483.Google Scholar
Oddy, M., & da Silva Ramos, S. (2013). The clinical and cost-benefits of investing in neurobehavioural rehabilitation: A multi-centre study. Brain Injury, 27 (13–14), 1500–1507.Google Scholar
Pietrapiana, P., Tamietto, M., Torrini, G., Mezzanato, T., Rago, R., & Perino, C. (2005). Role of premorbid factors in predicting safe return to driving after severe TBI. Brain Injury, 19 (3), 197–211.Google Scholar
Rapport, L.J., Hanks, R.A., & Bryer, R.C. (2006). Barriers to driving and community integration after traumatic brain injury. The Journal of Head Trauma Rehabilitation, 21 (1), 34–44.Google Scholar
Ross, P.E., Ponsford, J.L., Di Stefano, M., & Spitz, G. (2015). Predictors of on-road driver performance following traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 96 (3), 440–446.Google Scholar
Scholten, A.C., Haagsma, J.A., Panneman, M.J., Van Beeck, E.F., & Polinder, S. (2014). Traumatic brain injury in the Netherlands: Incidence, costs and disability-adjusted life years. PLoS one, 9 (10), e110905.Google Scholar
Thornton, M., & Travis, S.S. (2003). Analysis of the reliability of the Modified Caregiver Strain Index. The Journal of Gerontology, Series B, Psychological Sciences and Social Sciences, 58 (2), S129Google Scholar
van Heugten, C.M., Geurtsen, G.J., Derksen, R.E., Martina, J.D., Geurts, A.C., & Evers, S.M. (2011). Intervention and societal costs of residential community reintegration for patients with acquired brain injury: A cost-analysis of the Brain Integration Programme. Journal of Rehabilitation Medicine, 43 (7), 647–652.Google Scholar
Vos T, F.A., Naghavi, M., Lozano, R., Michaud, C., Ezzati, M., Shibuya, K. . . . Abraham, J. (2013). Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. The Lancet, 380, 9859 2163–2196.Google Scholar
World Health Organization (WHO) (2001) International Classification of Functioning, Disability and Health. Geneva: WHO.Google Scholar
Williams, M.W., Rapport, L.J., Millis, S.R., & Hanks, R.A. (2014). Psychosocial outcomes after traumatic brain injury: Life satisfaction, community integration, and distress. Rehabilitation Psychology, 59 (3), 298.Google Scholar
Wood, R.L., McCrea, J., Wood, L., & Merriman, R. (1999). Clinical and cost effectiveness of post-acute neurobehavioural rehabilitation. Brain Injury, 13 (2), 69–88.Google Scholar
Worthington, A.D., Matthews, S., Melia, Y., & Oddy, M. (2006). Cost-benefits associated with social outcome from neurobehavioural rehabilitation. Brain Injury, 20 (9), 947–957.Google Scholar