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The Structure of the Rivermead Post-Concussion Symptoms Questionnaire in Australian Adults with Traumatic Brain Injury

Published online by Cambridge University Press:  12 December 2017

Matt Thomas*
Affiliation:
School of Psychology, Charles Sturt University, Bathurst, NSW, Australia Neurotrama Register of Tasmania, Royal Hobart Hospital, TAS, Australia
Clive Skilbeck
Affiliation:
Neurotrama Register of Tasmania, Royal Hobart Hospital, TAS, Australia School of Psychology, University of Tasmania, Hobart, TAS, Australia
Phillipa Cannan
Affiliation:
Neurotrama Register of Tasmania, Royal Hobart Hospital, TAS, Australia School of Psychology, University of Tasmania, Hobart, TAS, Australia
Mark Slatyer
Affiliation:
Neurotrama Register of Tasmania, Royal Hobart Hospital, TAS, Australia
*
Address for correspondence: Dr Matt Thomas, School of Psychology, Charles Sturt University Bathurst, New South Wales, Australia. E-mail: mathomas@csu.edu.au
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Abstract

Background and aims: Many sustaining traumatic brain injury (TBI) suffer ongoing post-concussion symptoms (PCS). The Rivermead Post-Concussion Symptoms Questionnaire (RPQ) is widely used, although there is disagreement about its structure. This study compared the fit of published RPQ structures with a four-factor structure derived from a large adult sample with TBI in Tasmania.

Method: 661 adults with TBI completed the RPQ at approximately one month post injury. Exploratory factor analysis (EFA), using the first half of the sample (n = 330), suggested a four-factor solution. This was compared with models reported in the literature with the second half of the sample (n = 331), using structural equation modelling. Trajectory of recovery across these factors was examined within subsamples at 1, 3, 6 and 12 months following TBI.

Results: Inter-correlations between items were strongest for somatic, cognitive and emotional functioning items and the EFA identified a four-factor model. Fit was examined utilising bootstrapping for model comparison. The data at 1 month following TBI best fitted the four-factor model (CFI = .95, RMSEA = .060 (.049–.071) and factors had adequate internal consistency (r = .61–.89). This model appeared a good fit and clinically useful across time points to 12 months post injury.

Conclusions: Data best fitted a four-factor model, identified using a rigorous statistical approach. Clinicians and clinical researchers may use this preferred model to provide more specific measurement of the severity of PCS. Future research could attempt replication within international samples.

Type
Articles
Copyright
Copyright © Australasian Society for the Study of Brain Impairment 2017 

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References

AIHW. (2007). Disability in Australia: Acquired brain injury. Canberra: AIHWGoogle Scholar
Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52 (3), 317332.Google Scholar
Arbuckle, J. L. (2007). Amos 16.0 User's Guide. Chicago: SPSS.Google Scholar
Barker-Collo, S., Jones, K., Theadom, A., Starkey, N., Dowell, A., McPherson, K., . . . Feigin, V. (2015). Neuropsychological outcome and its correlates in the first year after adult mild traumatic brain injury: A population-based New Zealand study. Brain Injury, 29 (13–14), 16041616.Google Scholar
Bell, K.R., Hoffman, J.M., Temkin, N.R., Powell, J.M., Fraser, R.T., Esselman, P.C., . . . Dikmen, S. (2008). The effect of telephone counselling on reducing post-traumatic symptoms after mild traumatic brain injury: A randomised trial. Journal of Neurology, Neurosurgery & Psychiatry, 79 (11), 12751281.Google Scholar
Bentler, P.M. (1988). Comparative fit indices in structural models. Psychological Bulletin, 107, 238246.Google Scholar
Bentler, P.M., & Bonnet, D.G. (1980). Significance tests and the goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88, 588606.Google Scholar
Browne, M.W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Testing structural equation models. Newbury Park, CA: Sage.Google Scholar
Byrne, B. (2013). Structural equation modelling with AMOS: Basic concepts, application and programming. New York: Routledge.Google Scholar
Carroll, L., Cassidy, J.D., Cancelliere, C., Côté, P., Hincapié, C.A., Kristman, V.L., . . . Hartvigsen, J. (2014). Systematic review of the prognosis after mild traumatic brain injury in adults: Cognitive, psychiatric, and mortality outcomes: Results of the International Collaboration on Mild Traumatic Brain Injury Prognosis. Archives of Physical Medicine and Rehabilitation, 95 (3), S152S173.Google Scholar
Carroll, L., Cassidy, J.D., Peloso, P., Borg, J., Von Holst, H., Holm, L., . . . Pépin, M. (2004). Prognosis for mild traumatic brain injury: Results of the WHO collaborating centre task force on mild traumatic brain injury. Journal of Rehabilitation Medicine, 36 (0), 84105.Google Scholar
Cassidy, J.D., Carroll, L.J., Peloso, P.M., Borg, J., Von Holst, H., Holm, L., . . . Coronado, V.G. (2004). Incidence, risk factors and prevention of mild traumatic brain injury: Results of the WHO collaborating centre task force on mild traumatic brain injury. Journal of Rehabilitation Medicine, 43 Suppl, 2860.Google Scholar
Cnossen, M.C., Winkler, E.A., Yue, J.K., Okonkwo, D.O., Valadka, A., Steyerberg, E.W., . . . Manley, G.T. (2017). Development of a Prediction model for post-concussive symptoms following mild traumatic brain injury: A TRACK-TBI pilot study. Journal of Neurotrauma(ja), 34 (16): 23962409.Google Scholar
Dean, P.J., O'Neill, D., & Sterr, A. (2012). Post-concussion syndrome: Prevalence after mild traumatic brain injury in comparison with a sample without head injury. Brain Injury, 26 (1), 1426.Google Scholar
Department of Veterans Affairs and Department of Defense (2009). Clinical Practice Guideline: Management of Concussion/mild Traumatic Brain Injury. Available at: https://www.healthquality.va.gov/guidelines/Rehab/mtbi/mTBICPGFullCPG50821816.pdf.Google Scholar
Dexheimer, J.W., Kurowski, B.G., Anders, S.H., McClanahan, N., Wade, S.L., & Babcock, L. (2017). Usability evaluation of the SMART application for youth with mTBI. International Journal of Medical Informatics, 97, 163170.Google Scholar
Dikmen, S., Machamer, J., Fann, J.R., & Temkin, N.R. (2010). Rates of symptom reporting following traumatic brain injury. Journal of the International Neuropsychological Society, 16 (03), 401411.Google Scholar
Elgmark Andersson, E., Emanuelson, I., Björklund, R., & Stålhammar, D.A. (2007). Mild traumatic brain injuries: The impact of early intervention on late sequelae. A randomized controlled trial. Acta Neurochirurgica, 149 (2), 151160.Google Scholar
Eyres, S., Carey, A., Gilworth, G., Neumann, V., & Tennant, A. (2005). Construct validity and reliability of the Rivermead Post Concussion Symptoms Questionnaire. Clinical Rehabilitation, 19, 878887.Google Scholar
Faux, S., & Sheedy, J. (2008). A prospective controlled study in the prevalence of posttraumatic headache following mild traumatic brain injury. Pain Medicine, 9 (8), 10011011.Google Scholar
Finney, S., & DiStefano, C. (2006). Non-normal and categorical data in structural equation modelling. Greenwich, CT: Age Publishing.Google Scholar
Folstein, M.L., Folstein, S.E., & McHugh, P.R. (1975). Mini-mental state: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatry Research, 12, 189198.Google Scholar
Fortune, N., & Wen, X. (1999). The definition, incidence and prevalence of acquired brain injury in Australia. Canberra: Australian Institute Of Health And Welfare.Google Scholar
Ghaffar, O., McCullagh, S., Ouchterlony, D., & Feinstein, A. (2006). Randomized treatment trial in mild traumatic brain injury. Journal of Psychosomatic Research, 61 (2), 153160.Google Scholar
Hadanny, A., & Efrati, S. (2016). Treatment of persistent post-concussion syndrome due to mild traumatic brain injury: Current status and future directions. Expert Review of Neurotherapeutics, 16 (8), 875887. doi:10.1080/14737175.2016.1205487Google Scholar
Herrmann, N., Rapoport, M.J., Rajaram, R.D., Chan, F., Kiss, A., Ma, A.K., . . . Lanctôt, K.L. (2009). Factor analysis of the Rivermead Post-Concussion symptoms questionnaire in mild-to-moderate traumatic brain injury patients. The Journal of Neuropsychiatry and Clinical Neurosciences, 21 (2), 181188.Google Scholar
Hillier, S.J., Hiller, J.E., & Metzer, J. (1997). Epidemiology of traumatic brain injury. Brain Injury, 11 (9), 649659.Google Scholar
Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6 (1), 155.Google Scholar
Kim, H., & Millsap, R. (2014). Using the bollen-stine bootstrapping method for evaluating approximate fit indices. Multivariate Behavioral Research, 49 (6), 581596.Google Scholar
King, N. (2014). A systematic review of age and gender factors in prolonged post-concussion symptoms after mild head injury. Brain Injury, 28 (13–14), 16391645.Google Scholar
King, N., Crawford, S., Wenden, F.J., Moss, N.E., & Wade, D.T. (1995). The Rivermead Post Concussion Symptoms Questionnaire: A measure of symptoms commonly experienced after head injury and its reliability. Journal of Neurology, 242, 587592.Google Scholar
King, N., Wenden, F.J., Caldwell, F.E., & Wade, D.T. (1999). Early prediction of persisting post-concussion symptoms following mild and moderate head injuries. British Journal of Clinical Psychology, 38 (1), 1525.Google Scholar
Kleffelgaard, I., Roe, C., Soberg, H.L., & Bergland, A. (2012). Associations among self-reported balance problems, post-concussion symptoms and performance-based tests: A longitudinal follow-up study. Disability and Rehabilitation, 34 (9), 788794.Google Scholar
Kraus, J.F., Hsu, P., Schafer, K., & Afifi, A. (2014). Sustained outcomes following mild traumatic brain injury: Results of a five-emergency department longitudinal study. Brain Injury, 28 (10), 12481256.Google Scholar
Laborey, M., Masson, F., Ribéreau-Gayon, R., Zongo, D., Salmi, L.R., & Lagarde, E. (2014). Specificity of postconcussion symptoms at 3 months after mild traumatic brain injury: Results from a comparative cohort study. The Journal of Head Trauma Rehabilitation, 29 (1), E28–E36.Google Scholar
Langley, J., Johnson, S., Slatyer, M., Skilbeck, C.E., & Thomas, M. (2010). Issues of loss to follow-up in a population study of traumatic brain injury (TBI) followed to 3 years post-trauma. Brain Injury, 24 (7–8), 939947.Google Scholar
Lannsjö, M., Borg, J., Björklund, G., Af Geijerstam, J.-L., & Lundgren-Nilsson, Å. (2011). Internal construct validity of the rivermead post-concussion symptoms questionnaire. Journal of Rehabilitation Medicine, 43 (11), 9971002.Google Scholar
Lannsjö, M., Geijerstam, J.-L.A., Johansson, U., Bring, J., & Borg, J. (2009). Prevalence and structure of symptoms at 3 months after mild traumatic brain injury in a national cohort. Brain Injury, 23 (3), 213219.Google Scholar
Linhart, H., & Zuchini, W. (1986). Model selection. New York, USA: John Wiley.Google Scholar
Lundin, A., de Boussard, C., Edman, G., & Borg, J. (2006). Symptoms and disability until 3 months after mild TBI. Brain Injury, 20 (8), 799806.Google Scholar
Matuseviciene, G., Borg, J., Stålnacke, B.-M., Ulfarsson, T., & de Boussard, C. (2013). Early intervention for patients at risk for persisting disability after mild traumatic brain injury: A randomized, controlled study. Brain Injury, 27 (3), 318324.Google Scholar
Menon, D.K., Schwab, K., Wright, D.W., & Maas, A.I. (2010). Position statement: Definition of traumatic brain injury. Archives of Physical and Medical Rehabilitation, 91 (11), 16371640.Google Scholar
Naeser, M.A., Zafonte, R., Krengel, M.H., Martin, P.I., Frazier, J., Hamblin, M.R., . . . Baker, E.H. (2014). Significant improvements in cognitive performance post-transcranial, red/near-infrared light-emitting diode treatments in chronic, mild traumatic brain injury: Open-protocol study. Journal of Neurotrauma, 31 (11), 10081017.Google Scholar
Ponsford, J., Sloane, S., & Snow, P. (2013). Traumatic brain injury: Rehabilitation for everyday adaptive living. East Sussex, UK: Psychology Press.Google Scholar
Ponsford, J., Willmott, C., Rothwell, A., Cameron, P., Kelly, A.-M., Nelms, R., . . . Ng, K. (2000). Factors influencing outcome following mild traumatic brain injury in adults. Journal of the International Neuropsychological Society, 6 (5), 568579.Google Scholar
Ponsford, J., Ziino, C., Parcell, D., Shekleton, J., Roper, M., Redman, J., . . . Rajaratnam, S. (2012). Fatigue and sleep disturbance following traumatic brain injury—their nature, causes, and potential treatments. The Journal of Head Trauma Rehabilitation, 27 (3), 224233.Google Scholar
Potter, S., Leigh, E., Wade, D., & Fleminger, S. (2006). The Rivermead Post Concussion Symptoms Questionnaire. Journal of Neurology, 253 (12), 16031614.Google Scholar
Rabinowitz, A.R., Li, X., McCauley, S.R., Wilde, E.A., Barnes, A., Hanten, G., . . . Levin, H.S. (2015). Prevalence and predictors of poor recovery from mild traumatic brain injury. Journal of Neurotrauma, 32 (19), 14881496.Google Scholar
Randall, D., Thomas, M., Whiting, D., & McGrath, A. (2016). Depression anxiety stress scales (DASS-21): Factor structure in traumatic brain injury rehabilitation. Journal of Head Trauma Rehabilitation.Google Scholar
Relander, M., Troupp, H., & Af Björkesten, G. (1972). Controlled trial of treatment for cerebral concussion. British Medical Journal, 4 (5843), 777.Google Scholar
Ryan, L.M., & Warden, D.L. (2003). Post concussion syndrome. International Review of Psychiatry, 15, 310316.Google Scholar
Smith-Seemiller, L., Fow, N. R., Kant, R., & Franzen, M.D. (2003). Presence of post-concussion syndrome symptoms in patients with chronic pain vs mild traumatic brain injury. Brain Injury, 17 (3), 199206.Google Scholar
Sullivan, K.A., & Garden, N. (2011). A comparison of the psychometric properties of 4 postconcussion syndrome measures in a nonclinical sample. Journal of Head Trauma Rehabilitation, 26 (2), 170176.Google Scholar
Tabachnick, L.S., & Fidell, L.S. (2013). Using multivariate statistics (6th ed.). New York: Pearson.Google Scholar
Tate, R. (2010). A compendium of tests, scales, and questionnaires: The practitioner's guide to measuring outcomes after acquired brain impairment. New York: Psychology Press.Google Scholar
Tate, R., McDonald, S., & Lulham, J. (1998). Incidence of hospital-treated traumatic brain injury in an Australian community. Australian and New Zealand journal of Public Health, 22, 419423.Google Scholar
Theadom, A., Parag, V., Dowell, T., McPherson, K., Starkey, N., Barker-Collo, S., . . . Group, B.R. (2016). Persistent problems 1 year after mild traumatic brain injury: A Longitudinal population study in New Zealand. Br J Gen Pract, 66 (642), e16e23.Google Scholar
Thomas, M.D., McGrath, A., & Skilbeck, C.E. (2012). The psychometric properties of the quality of life inventory in an Australian community sample. Australian Journal of Psychology. doi: 10.1111/j.1742-9536.2012.00054.xGoogle Scholar
Ullman, J. B. (2001). Structural equation modeling. In Tabachnick, L.S. & Fidell, L.S. (Eds.), Using multivariate statistics (4th ed.). MA: Allyn & Bacon.Google Scholar
Wade, D., Crawford, S., Wenden, F., King, N., & Moss, N. (1997). Does routine follow up after head injury help? A randomised controlled trial. Journal of Neurology, Neurosurgery & Psychiatry, 62 (5), 478484.Google Scholar
Wade, D., King, N., Wenden, F., Crawford, S., & Caldwell, F. (1998). Routine follow up after head injury: A second randomised controlled trial. Journal of Neurology, Neurosurgery & Psychiatry, 65 (2), 177183.Google Scholar