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Factor structure and measurement invariance of post-concussion symptom ratings on the Health and Behaviour Inventory across time, raters, and groups: An A-CAP study

Published online by Cambridge University Press:  04 August 2022

Cherri Zhang
Department of Psychology, University of Calgary, Calgary, AB, Canada
Ken Tang
Independent Statistical Consultant, Richmond, BC, Canada
Roger Zemek
Children’s Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada Department of Pediatrics and Emergency Medicine, University of Ottawa, Ottawa, ON, Canada
Miriam H. Beauchamp
Department of Psychology, Université de Montréal, Montreal, QC, Canada Centre Hospitalier Universitaire Sainte-Justine, Montreal, QC, Canada
William Craig
Department of Pediatrics, University of Alberta, and Stollery Children’s Hospital, Edmonton, AB, Canada
Quynh Doan
Department of Pediatrics, University of British Columbia, and BC Children’s Hospital Research Institute, Vancouver, BC, Canada
Keith Owen Yeates*
Department of Psychology, University of Calgary, Calgary, AB, Canada Alberta Children’s Hospital Research Institute and Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
Corresponding author: Keith O. Yeates, Email:



To validate the two-factor structure (i.e., cognitive and somatic) of the Health and Behaviour Inventory (HBI), a widely used post-concussive symptom (PCS) rating scale, through factor analyses using bifactor and correlated factor models and by examining measurement invariance (MI).


PCS ratings were obtained from children aged 8–16.99 years, who presented to the emergency department with concussion (n = 565) or orthopedic injury (OI) (n = 289), and their parents, at 10-days, 3-months, and 6-months post-injury. Item-level HBI ratings were analyzed separately for parents and children using exploratory and confirmatory factor analyses (CFAs). Bifactor and correlated models were compared using various fit indices and tested for MI across time post-injury, raters (parent vs. child), and groups (concussion vs. OI).


CFAs showed good fit for both a three-factor bifactor model, consisting of a general factor with two subfactors (i.e., cognitive and somatic), and a correlated two-factor model with cognitive and somatic factors, at all time points for both raters. Some results suggested the possibility of a third factor involving fatigue. All models demonstrated strict invariance across raters and time. Group comparisons showed at least strong or strict invariance.


The findings support the two symptom dimensions measured by the HBI. The three-factor bifactor model showed the best fit, suggesting that ratings on the HBI also can be captured by a general factor. Both correlated and bifactor models showed substantial MI. The results provide further validation of the HBI, supporting its use in childhood concussion research and clinical practice.

Research Article
Copyright © INS. Published by Cambridge University Press, 2022

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Agtarap, S., Kramer, M. D., Campbell-Sills, L., Yuh, E., Mukherjee, P., Manley, G. T., … Nelson, L. D. (2020). Invariance of the Bifactor Structure of Mild Traumatic Brain Injury (mTBI) Symptoms on the Rivermead Postconcussion symptoms questionnaire across time, demographic characteristics, and clinical groups: A TRACK-TBI study. Assessment. Google ScholarPubMed
Ayr, L. K., Yeates, K. O., Taylor, H. G., & Browne, M. (2009). Dimensions of postconcussive symptoms in children with mild traumatic brain injuries. Journal of the International Neuropsychological Society, 15, 1930. CrossRefGoogle ScholarPubMed
Babl, F. E., Dionisio, D., Davenport, L., Baylis, A., Hearps, S. J. C., Bressan, S., … Davis, G. A. (2017). Accuracy of components of SCAT to identify children with concussion. Pediatrics, 140. CrossRefGoogle ScholarPubMed
Barlow, K. M., Crawford, S., Stevenson, A., Sandhu, S. S., Belanger, F., & Dewey, D. (2010). Epidemiology of postconcussion syndrome in pediatric mild traumatic brain injury. Pediatrics, 126, e374e381. CrossRefGoogle ScholarPubMed
Beauchamp, M. H., Tang, K., Yeates, K. O., Anderson, P., Brooks, B. L., Keightley, M., … Zemek, R.L. (2019). Predicting wellness after pediatric concussion. Journal of the International Neuropsychological Society, 25, 375389. CrossRefGoogle ScholarPubMed
Bialy, L., Plint, A., Zemek, R., Johnson, D., Klassen, T., Osmond, M., … Pediatric Emergency Research, C. (2018). Pediatric emergency research Canada: Origins and evolution. Pediatric Emergency Care, 34, 138144. CrossRefGoogle ScholarPubMed
Brett, B. L., Kramer, M. D., McCrea, M. A., Broglio, S. P., McAllister, T. W., Nelson, L. D., … Susmarski, A. (2020). Bifactor model of the sport concussion assessment tool symptom checklist: Replication and invariance across time in the CARE consortium sample. American Journal of Sports Medicine, 48, 27832795. CrossRefGoogle ScholarPubMed
Broglio, S. P., Kontos, A. P., Levin, H., Schneider, K., Wilde, E. A., Cantu, R. C., … Joseph, K. (2018). National institute of neurological disorders and stroke and department of defense sport-related concussion common data elements version 1.0 recommendations. Journal of Neurotrauma, 35, 27762783. CrossRefGoogle ScholarPubMed
Browne, M. (2001). An overview of analytic rotation in exploratory factor analysis. Multivariate Behavioral Research, 36, 111150.CrossRefGoogle Scholar
Bryan, M. A., Rowhani-Rahbar, A., Comstock, R. D., Rivara, F., & Seattle Sports Concussion Research, C. (2016). Sports- and recreation-related concussions in US youth. Pediatrics, 138. CrossRefGoogle ScholarPubMed
Carroll, L. J., Cassidy, J. D., Holm, L., Kraus, J., & 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. Journal of Rehabilitation Medicine (43 Suppl), 113125. CrossRefGoogle ScholarPubMed
Chen, F. F., Hayes, A., Carver, C. S., Laurenceau, J. P., & Zhang, Z. (2012). Modeling general and specific variance in multifaceted constructs: A comparison of the bifactor model to other approaches. Journal of Personality, 80, 219251. CrossRefGoogle ScholarPubMed
Davis, G. A., Purcell, L., Schneider, K. J., Yeates, K. O., Gioia, G. A., Anderson, V., … Kutcher, J. S. (2017). The child sport concussion assessment tool 5th edition (Child SCAT5): Background and rationale. British Journal of Sports Medicine, 51, 859861. Google ScholarPubMed
Dupont, D., Beaudoin, C., Desire, N., Tran, M., Gagnon, I., & Beauchamp, M. H. (2021). Report of early childhood traumatic injury observations & symptoms: Preliminary validation of an observational measure of post-concussive symptoms. Journal of Head Trauma Rehabilitation. Google Scholar
Franke, L. M., Czarnota, J. N., Ketchum, J. M., & Walker, W. C. (2015). Factor analysis of persistent post-concussive symptoms within a military sample with blast exposure. Journal of Head Trauma Rehabilitation, 30, E34E46. CrossRefGoogle ScholarPubMed
Hajek, C. A., Yeates, K. O., Taylor, H. G., Bangert, B., Dietrich, A., Nuss, K. E., … Wright, M. (2011). Agreement between parents and children on ratings of post-concussive symptoms following mild traumatic brain injury. Child Neuropsychology, 17, 1733. CrossRefGoogle ScholarPubMed
Hilt, R. J., McCarty, C. A., Rivara, F. P., Wang, J., Marcynyszyn, L. A., Chrisman, S. P. D., … Zatzick, D. F. (2022). Exploring heterogeneity of stepped collaborative care treatment response trajectories after adolescent sports injury concussion. Psychiatry, 112. Google ScholarPubMed
Joyce, A. S., Labella, C. R., Carl, R. L., Lai, J. S., & Zelko, F. A. (2015). The post-concussion symptom scale: Utility of a three-factor structure. Medicine & Science in Sports & Exercise, 47, 11191123. CrossRefGoogle ScholarPubMed
Karr, J. E., & Iverson, G. L. (2020). The structure of post-concussion symptoms in adolescent student athletes: confirmatory factor analysis and measurement invariance. The Clinical Neuropsychologist, 140. Google ScholarPubMed
Liu, Y., Millsap, R. E., West, S. G., Tein, J. Y., Tanaka, R., & Grimm, K. J. (2017). Testing measurement invariance in longitudinal data with ordered-categorical measures. Psychological Methods, 22(3), 486506. CrossRefGoogle ScholarPubMed
Lumba-Brown, A., Yeates, K. O., Sarmiento, K., Breiding, M. J., Haegerich, T. M., Gioia, G. A., … Timmons, S. D. (2018). Centers for disease control and prevention guideline on the diagnosis and management of mild traumatic brain injury among children. JAMA Pediatrics, 172, e182853. CrossRefGoogle ScholarPubMed
McCarty, C. A., Zatzick, D. F., Marcynyszyn, L. A., Wang, J., Hilt, R., Jinguji, T., … Rivara, F. P. (2021). Effect of collaborative care on persistent post-concussive symptoms in adolescents: A randomized clinical trial. JAMA Network Open, 4, e210207. CrossRefGoogle ScholarPubMed
McCauley, S. R., Wilde, E. A., Anderson, V. A., Bedell, G., Beers, S. R., Campbell, T. F., … Yeates, K. O. (2012). Recommendations for the use of common outcome measures in pediatric traumatic brain injury research. Journal of Neurotrauma, 29, 678705. CrossRefGoogle ScholarPubMed
Medicine, AftAoA. (1990). The abbreviated injury scale. Retrieved June 16 from Google Scholar
Merritt, V. C., & Arnett, P. A. (2014). Premorbid predictors of postconcussion symptoms in collegiate athletes. Journal of Clinical and Experimental Neuropsychology, 36, 10981111. CrossRefGoogle ScholarPubMed
Moran, L. M., Taylor, H. G., Rusin, J., Bangert, B., Dietrich, A., Nuss, K. E., … Yeates, K. O. (2012). Quality of life in pediatric mild traumatic brain injury and its relationship to postconcussive symptoms. Journal of Pediatric Psychology, 37, 736744. CrossRefGoogle ScholarPubMed
Nelson, L. D., Kramer, M. D., Patrick, C. J., & McCrea, M. A. (2018). Modeling the structure of acute sport-related concussion symptoms: A Bifactor approach. Journal of the International Neuropsychological Society, 24, 793804. CrossRefGoogle ScholarPubMed
Novak, Z., Aglipay, M., Barrowman, N., Yeates, K. O., Beauchamp, M. H., Gravel, J., … Zemek, R. L. (2016). Association of persistent post-concussion symptoms With pediatric quality of life. JAMA Pediatr, 170, e162900. CrossRefGoogle ScholarPubMed
O’Neill, J. A., Rose, S. C., Davidson, A. M., Shiplett, K. M., Castillo, A., & McNally, K. A. (2021). Predictors of treatment response to multidisciplinary care for persistent symptoms after pediatric concussion. Developmental Neurorehabilitation, 17. Google ScholarPubMed
O’Brien, H., Minich, N. M., Langevin, L. M., Taylor, H. G., Bigler, E. D., Cohen, D. M., … Yeates, K. O. (2021). Normative and psychometric characteristics of the Health and Behavior Inventory among children with mild orthopedic injury presenting to the emergency department: Implications for assessing post-concussive symptoms using the Child Sport Concussion Assessment Tool 5th edition (Child SCAT5). Clinical Journal of Sport Medicine, 31, e221e228. CrossRefGoogle Scholar
Patsimas, T., Howell, D. R., Potter, M. N., Provance, A. J., Kirkwood, M. W., & Wilson, J. C. (2020). Concussion-symptom rating correlation between pediatric patients and their parents. Journal of Athletic Training, 55, 10201026. CrossRefGoogle ScholarPubMed
Piland, S. G., Motl, R. W., Ferrara, M. S., & Peterson, C. L. (2003). Evidence for the factorial and construct validity of a self-report concussion symptoms scale. Journal of Athletic Training, 38, 104112. Google ScholarPubMed
Putnick, D. L., & Bornstein, M. H. (2016). Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review, 41, 7190. CrossRefGoogle ScholarPubMed
Reed, N. Z. R., Dawson, J., Ledoux, AA, et al. (2019). Living guideline for diagnosing and managing pediatric concussion. Ontario Neurotrauma Foundation. Google Scholar
Reise, S. P. (2012). Invited paper: The rediscovery of Bifactor measurement models. Multivariate Behavioral Research, 47, 667696. CrossRefGoogle ScholarPubMed
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Evaluating bifactor models: Calculating and interpreting statistical indices. Psychological Methods, 21, 137150. CrossRefGoogle ScholarPubMed
Sady, M. D., Vaughan, C. G., & Gioia, G. A. (2014). Psychometric characteristics of the postconcussion symptom inventory in children and adolescents. Archives of Clinical Neuropsychology, 29, 348363. CrossRefGoogle ScholarPubMed
Taylor, H. G., Dietrich, A., Nuss, K., Wright, M., Rusin, J., Bangert, B., … Yeates, K. O. (2010). Post-concussive symptoms in children with mild traumatic brain injury. Neuropsychology, 24, 148159. CrossRefGoogle ScholarPubMed
Waljas, M., Iverson, G. L., Hartikainen, K. M., Liimatainen, S., Dastidar, P., Soimakallio, S., … Ohman, J. (2012). Reliability, validity and clinical usefulness of the BNI fatigue scale in mild traumatic brain injury. Brain Injury, 26, 972978. CrossRefGoogle ScholarPubMed
Yeates, K. O., Beauchamp, M., Craig, W., Doan, Q., Zemek, R., Bjornson, B., … Schneider, K. J. (2017). Advancing concussion assessment in pediatrics (A-CAP): A prospective, concurrent cohort, longitudinal study of mild traumatic brain injury in children: Protocol study. BMJ Open, 7, e017012. CrossRefGoogle Scholar
Yeates, K. O., Kaizar, E., Rusin, J., Bangert, B., Dietrich, A., Nuss, K., … Taylor, H. G. (2012). Reliable change in postconcussive symptoms and its functional consequences among children with mild traumatic brain injury. Archives of Pediatrics and Adolescent Medicine, 166, 615622. CrossRefGoogle ScholarPubMed
Zemek, R., Barrowman, N., Freedman, S. B., Gravel, J., Gagnon, I., McGahern, C., … Osmond, M. (2016). Clinical risk score for persistent post-concussion symptoms among children with acute concussion in the ED. JAMA, 315, 10141025. CrossRefGoogle ScholarPubMed
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