Is the Rivermead Post-Concussion Symptoms Questionnaire a Reliable and Valid Measure to Assess Long-Term Symptoms in Traumatic Brain Injury and Orthopedic Injury Patients? A Novel Investigation Using Rasch Analysis

Shivanthi Balalla, Chris Krägeloh, Oleg Medvedev, Richard Siegert, Shivanthi Balalla, Chris Krägeloh, Oleg Medvedev, Richard Siegert

Abstract

Persistent post-concussion syndrome (PCS) symptoms are known to last years after traumatic brain injury (TBI), and similar symptoms are increasingly being documented among those who have not experienced a TBI. There remains however, a dearth of empirical evidence on the structural composition of symptoms beyond the post-acute symptom phase after TBI, and little is known about the potential use of PCS symptom scales to measure PCS-like symptoms in non-TBI individuals. Our objective was therefore to examine the psychometric performance and dimensionality of the Rivermead Post-Concussion Symptoms Questionnaire (RPQ) as a measure of long-term PCS symptoms among a TBI and non-TBI sample. A case-control sample of 223 patients with injury, consisting of age- and sex-matched TBI participants (n = 109) and orthopedic participants (n = 114) were recruited from a regional trauma registry in New Zealand (NZ), and assessed at mean 2.5 years post-injury. Results from the Rasch analysis showed that the RPQ achieved fit to the Rasch model, demonstrating very good reliability (Person Separation Index [PSI] = 0.87), thereby indicating that the measure can be used reliably for individual and group assessment of symptoms among both TBI and orthopedic patients. In this study we demonstrated evidence of a unidimensional construct of PCS symptoms in both groups, which helps alleviate previous uncertainty about factor structure, and permits the calculation of a total RPQ score. Conversion of ordinal to interval total scores presented within are recommended for clinicians and researchers, to improve instrument precision, and to facilitate the interpretation of change scores and use of parametric methods in data analysis.

Keywords: Rasch analysis; brain injuries; orthopedic injuries; post-concussion syndrome; psychometrics.

Conflict of interest statement

No competing financial interests exist.

© Shivanthi Balalla et al., 2020; Published by Mary Ann Liebert, Inc.

Figures

FIG. 1.
FIG. 1.
Person-item threshold distribution for the 16-item RPQ. The blue bars indicate the TBI subsample (n = 109) and the red bars the orthopedic subsample (n = 114). In the top half, negative values (locations) represent individuals on the lower end of the PCS symptoms spectrum, whereas in the bottom half, negative locations indicate items that were most frequently endorsed by the sample. Conversely, positive locations indicate those with higher levels of PCS symptoms, or items that were least readily endorsed by respondents. PCS, post-concussion syndrome; RPQ, Rivermead Post-Concussion Symptoms Questionnaire; TBI, traumatic brain injury.

References

    1. Kahan, M., Jones, K.M., Balalla, S., McPherson, K., Stedman, E., and Feigin, V.L. (2018). Return to pre-injury work following mild traumatic brain injury. Brain Impairment 19, 153–165
    1. Balalla, S.K., Medvedev, O.N., Siegert, R.J., and Krägeloh, C.U. (2019). Validation of the WHOQOL-BREF and shorter versions using Rasch analysis in traumatic brain injury and orthopedic populations. . Med. Rehabil. 100, 1853–1862
    1. McMahon, P.J., Hricik, A., Yue, J.K., Puccio, A.M., Inoue, T., Lingsma, H.F., Beers, S.R., Gordon, W.A., Valadka, A.B., and Manley, G.T. (2014). Symptomatology and functional outcome in mild traumatic brain injury: results from the prospective TRACK-TBI study. J. Neurotrauma 31, 26–33
    1. Broshek, D.K., De Marco, A.P., and Freeman, J.R. (2015). A review of post-concussion syndrome and psychological factors associated with concussion. Brain Inj. 29, 228–237
    1. Cnossen, M.C., van der Naalt, J., Spikman, J.M., Nieboer, D., Yue, J.K., Winkler, E.A., Manley, G.T., von Steinbuechel, N., Polinder, S., Steyerberg, E.W., and Lingsma, H.F. (2018). Prediction of persistent post-concussion symptoms after mild traumatic brain injury. J. Neurotrauma 35, 2691–2698
    1. Hiploylee, C., Dufort, P.A., Davis, H.S., Wennberg, R.A., Tartaglia, M.C., Mikulis, D., Hazrati, L.-N., and Tator, C.H. (2017). Longitudinal study of postconcussion syndrome: not everyone recovers. J. Neurotrauma 34, 1511–1523
    1. O'Connor, C., Colantonio, A., and Polatajko, H. (2005). Long term symptoms and limitations of activity of people with traumatic brain injury: a ten-year follow-up. Psychol. Rep. 97, 169–179
    1. Theadom, A., Starkey, N., Barker-Collo, S., Jones, K., Ameratunga, S., and Feigin, V. (2018). Population-based cohort study of the impacts of mild traumatic brain injury in adults four years post-injury. PLoS One 13, e0191655.
    1. King, N.S., Crawford, S., Wenden, F.J., Moss, N.E.G., and Wade, D.T. (1995). The Rivermead Post Concussion Symptoms Questionnaire: a measure of symptoms commonly experienced after head injury and its reliability. J. Neurol. 242, 587–592
    1. Sullivan, K., and Garden, N. (2011). A comparison of the psychometric properties of 4 postconcussion syndrome measures in a nonclinical sample. J. Head Trauma Rehabil. 26, 170–176
    1. Eyres, S., Carey, A., Gilworth, G., Neumann, V., and Tennant, A. (2005). Construct validity and reliability of the Rivermead Post-Concussion Symptoms Questionnaire. Clin. Rehabil. 19, 878–887
    1. Lannsjö, M., Borg, J., Bjorklund, G., Af Geijerstam, J.L. and Lundgren-Nilsson, A. (2011). Internal construct validity of the Rivermead Post-Concussion Symptoms Questionnaire. J. Rehabil. Med. 43, 997–1002
    1. Barker-Collo, S., Theadom, A., Starkey, N.J., Kahan, M., Jones, K., and Feigin, V. (2019). Long-term factor structure of the Rivermead Post-Concussion Symptom Questionnaire in mild traumatic brain injury and normative sample. Brain Inj. 33, 618–622
    1. Potter, S., Leigh, E., Wade, D., and Fleminger, S. (2006). The Rivermead Post Concussion Symptoms Questionnaire. J. Neurol. 253, 1603–1614
    1. Fow, N.R., Kant, R., and Franzen, M.D. (2003). Presence of post-concussion syndrome symptoms in patients with chronic pain vs. mild traumatic brain injury. Brain Inj. 17, 199–206
    1. Iverson, G.L. (2006). Misdiagnosis of the persistent postconcussion syndrome in patients with depression. Arch. Clin. Neuropsychol. 21, 303–310
    1. Mickevičiene, D., Schrader, H., Obelieniene, D., Surkiene, D., Kunickas, R., Stovner, L.J., and Sand, T. (2004). A controlled prospective inception cohort study on the post-concussion syndrome outside the medicolegal context. Eur. J. Neurol. 11, 411–419
    1. Bond, T.G., and Fox, C.M. (2015). Applying the Rasch Model: Fundamental Measurement in the Human Sciences, 3rd ed. London: Routledge
    1. Leung, Y.-Y., Png, M.-E., Conaghan, P., and Tennant, A. (2014). A systematic literature review on the application of Rasch analysis in musculoskeletal disease—a special interest group report of OMERACT 11. J. Rheumatol. 41, 159–164
    1. Gennarelli, T.A., and Wodzin, E. (2006). AIS 2005: a contemporary injury scale. Injury 37, 1083–1091
    1. Carroll, L.J., Cassidy, J.D., Holm, L., Kraus, J., and Coronado, V.G. (2004). Methodological issues and research recommendations for mild traumatic brain injury: the WHO Collaborating Centre Task Force on Mild Traumatic Brain Injury. J. Rehabil. Med., 113–125
    1. Voormolen, D.C., Cnossen, M.C., Polinder, S., von Steinbuechel, N., Vos, P.E., and Haagsma, J.A. (2018). Divergent classification methods of post-concussion syndrome after mild traumatic brain injury: prevalence rates, risk factors, and functional outcome. J. Neurotrauma 35, 1233–1241
    1. Salvi, F., Miller, M.D., Grilli, A., Giorgi, R., Towers, A.L., Morichi, V., Spazzafumo, L., Mancinelli, L., Espinosa, E., Rappelli, A., and Dessì-Fulgheri, P. (2008). A manual of guidelines to score the modified cumulative illness rating scale and its validation in acute hospitalized elderly patients. J. Am. Geriatr. Soc. 56, 1926–1931
    1. Linacre, J.M. (1994). Sample size and item calibration stability. Rasch Meas. Trans. 7, 328
    1. Snell, D.L., Siegert, R.J., Debert, C.T., Cairncross, M., and Silverberg, N.D. (2020). Evaluation of the Fear Avoidance Behavior after Traumatic Brain Injury Questionnaire. J. Neurotrauma 37, 1566–1573
    1. Andrich, D., Sheridan, B., and Luo, G. (2009). RUMM2030. RUMM Laboratory: Perth, Australia
    1. Masters, G.N. (1982). A Rasch model for partial credit scoring. Psychometrika 47, 149–174
    1. Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika 43, 561–573
    1. Thomas, M., Skilbeck, C., Cannan, P., and Slatyer, M. (2018). The structure of the Rivermead Post-Concussion Symptoms Questionnaire in Australian adults with traumatic brain injury. Brain Impairment 19, 166–182
    1. Herrmann, N., Rapoport, M.J., Rajaram, R.D., Chan, F., Kiss, A., Ma, A.K., Feinstein, A., McCullagh, S. and Lanctot, K.L. (2009). Factor analysis of the Rivermead Post-Concussion Symptoms Questionnaire in mild-to-moderate traumatic brain injury patients. J. Neuropsychiatry Clin. Neurosci. 21, 181–188
    1. Barker-Collo, S., Theadom, A., Starkey, N., Kahan, M., Jones, K., and Feigin, V. (2018). Factor structure of the Rivermead Post-Concussion Symptoms Questionnaire over the first year following mild traumatic brain injury. Brain Inj. 32, 453–458
    1. Medvedev, O.N., Theadom, A., Barker-Collo, S., and Feigin, V. (2018). Distinguishing between enduring and dynamic concussion symptoms: applying generalisability theory to the Rivermead Post Concussion Symptoms Questionnaire (RPQ). PeerJ. 6, e5676.
    1. Chan, R.C. (2001). Base rate of post-concussion symptoms among normal people and its neuropsychological correlates. Clin. Rehabil. 15, 266–273
    1. Iverson, G.L., and Lange, R.T. (2003). Examination of “postconcussion-like” symptoms in a healthy sample. Appl. Neuropsychol. 10, 137–144
    1. Lishman, W.A. (1988). Physiogenesis and psychogenesis in the ‘post-concussional syndrome.’ Br. J. Psychiatry 153, 460–469
    1. Iverson, G., and Gaetz, M. (2004). Practical considerations for interpreting change following concussion, in: Traumatic Brain Injury in Sports: An International Neuropsychological Perspective. Lovell M.R., Echemendia R.J., Barth J., et al. (eds). Lisse, the Netherlands: Swets-Zeitlinger, pps. 323–356
    1. Meares, S., Shores, E.A., Taylor, A.J., Batchelor, J., Bryant, R.A., Baguley, I.J., Chapman, J., Gurka, J., Dawson, K., Capon, L., and Marosszeky, J.E. (2008). Mild traumatic brain injury does not predict acute postconcussion syndrome. J. Neurol. Neurosurg. Psychiatry 79, 300.
    1. Villemure, R., Nolin, P., and Le Sage, N. (2011). Self-reported symptoms during post-mild traumatic brain injury in acute phase: influence of interviewing method. Brain Inj. 25, 53–64
    1. Iverson, G.L. (2019). Network analysis and precision rehabilitation for the post-concussion syndrome. Front. Neurol. 10, 489.
    1. Reckase, M.D. (1979). Unifactor latent trait models applied to multifactor tests: Results and implications. J. Educ. Stat. 4, 207–230
    1. Wäljas, M., Iverson, G.L., Lange, R.T., Hakulinen, U., Dastidar, P., Huhtala, H., Liimatainen, S., Hartikainen, K., and Öhman, J. (2014). A prospective biopsychosocial study of the persistent post-concussion symptoms following mild traumatic brain injury. J. Neurotrauma 32, 534–547
    1. Meares, S., Shores, E.A., Taylor, A.J., Batchelor, J., Bryant, R.A., Baguley, I.J., Chapman, J., Gurka, J., Dawson, K., Capon, L., and Marosszeky, J.E. (2008). Mild traumatic brain injury does not predict acute postconcussion syndrome. J. Neurol. Neurosurg. Psychiatry 79, 300–306
    1. Barker-Collo, S.L., and Feigin, V.L. (2009). Capturing the spectrum: suggested standards for conducting population-based traumatic brain injury incidence studies. Neuroepidemiology 32, 1–3

Source: PubMed

Sponsorzy i współpracownicy

Warunki medyczne

Interwencje lekowe

3
Subskrybuj