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Effects of Media Sensationalization on Cognitive Performance and Post Concussive Symptoms

Published online by Cambridge University Press:  31 October 2018

Cara A. Bussell  and
Brandon E. Gavett
Cara A. Bussell
Affiliation:
University of Colorado ColoradoSprings
Brandon E. Gavett*
Affiliation:
University of Colorado ColoradoSprings
*
Correspondence and reprint requests to: Brandon E. Gavett. School of Psychological Science, University of Western Australia, 35 Stirling Highway, Crawley, Perth, WA 6009, Australia. Email: [email protected]
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Abstract

Objectives: The current study aimed to examine if televised media about mild traumatic brain injury (mTBI) framed in a sensationalized manner had a negative impact on cognitive functioning and persistent mTBI symptoms. Methods: One hundred two participants (MAge=37.16; SD=22.61) with a history of post-acute mTBI, recruited through a community research registry and an undergraduate recruitment system, were included in this study. Participants were assessed with a measure of health literacy, the Short Test of Functional Health Literacy in Adults (S-TOFHLA), and randomized to watch either a sensationalized or non-sensationalized news clip focused on mTBI. They were then assessed with the Paced Auditory Serial Addition Test (PASAT), Rivermead Post Concussion Symptoms Questionnaire (RPQ), Patient Reported Outcome Measures Information System (PROMIS) Depression scale, and the Posttraumatic Stress Disorder Checklist for the Diagnostic and Statistical Manual of Mental Disorders 5th edition (PCL-5). Results: Bayesian analyses indicated that sensationalized media—alone (βPASAT=−0.08; βRPQ=−0.08) or in the context of covariates (βPASAT=−0.11; βRPQ=−0.14)—was not a strong predictor of PASAT score or post-concussion syndrome symptom severity. Conclusions: Although media sensationalization of mTBI symptoms is not desirable, this study suggests that one brief exposure to sensationalized information may not have a meaningful immediate impact on the cognitive functioning or symptom reporting of individuals with a history of mTBI. Future research should examine long-term and downstream effects of sensationalized media reporting in samples with greater diversity of TBI history. (JINS, 2019, 25, 90–100)

Keywords

mTBIPCSStereotype threatNocebo effectDiagnosis threatConcussion
Type
Regular Research
Information
Journal of the International Neuropsychological Society , Volume 25 , Issue 1 , January 2019 , pp. 90 - 100
Copyright
Copyright © The International Neuropsychological Society 2018 

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References

REFERENCES

Assessment Center. (2015). PROMIS Depression Scoring Manual. Retrieved from https://www.assessmentcenter.net/documents/PROMIS Depression Scoring Manual.pdf Google Scholar
Baker, D.W., Williams, M.V., Parker, R.M., Gazmararian, J., & Nurss, J. (1999). Development of a brief test to measure functional health literacy. Patient Education and Counselling, 38(1), 33–42. doi:10.1016/S0738-3991(98)00116-5 Google Scholar
Bigler, E.D. (2008). Neuropsychology and clinical neuroscience of persistent post- concussive syndrome. Journal of International Neuropsychological Society, 14(1), 1–22. doi:10.1017/s135561770808017x Google Scholar
Blaine, H., Sullivan, K.A., & Edmed, S.L. (2013). The effect of varied test instructions on neuropsychological performance following mild traumatic brain injury: An investigation of “diagnosis threat.” Journal of Neurotrauma, 30, 1405–1414. doi:10.1089/neu.2013.2865 Google Scholar
Block, C., West, S., & Goldin, Y. (2016). Misconceptions and misattributions about traumatic brain injury: An integrated conceptual framework. Physical Medicine and Rehabilitation 8(1). doi:10.1016/j.pmrj.2015.05.022 Google Scholar
Bürkner, P. (2017) Bayesian Regression Models using Stan. R package version 1.7.0 Retrieved from http://mc-stan.org/ Google Scholar
Buschke, H., Kuslansky, G., Katz, M., Stewart, W.F., Sliwinski, M.J., Eckholdt, H.M., & Lipton, R.B. (1999). Screening for dementia with the Memory Impairment Screen. Neurology, 52(2), 231–238.Google Scholar
Carter-Allison, S.N., Potter, S., & Rimes, K. (2016). Diagnosis threat and injury beliefs after mild traumatic brain injury. Archives of Clinical Neuropsychology, 31(7), 727–737. doi:10.1093/arclin/acw062 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, 36(Suppl. 43), 28–60. doi:10.1080/16501960410023732 Google Scholar
Coleman, R., Thorson, E., & Wilkins, L. (2011). Testing the effect of framing and sourcing in health news stories. Journal of Health Communication, 16(9), 941–954. doi:10.1080/10810730.2011.561918 Google Scholar
Coppock, A. (2018). randomizr: Easy-to-use tools for common forms of random assignment and sampling. R package version 0.12.0. Retrieved from https://CRAN.R-project.org/package=randomizr Google Scholar
Delgado-Rodríguez, M., & Llorca, J., (2004). Bias. Journal of Epidemiology & Community Health, 58(8), 635–641. doi:10.1136/jech.2003.008466 Google Scholar
DiFazio, M., Silverberg, N.D., Kirkwood, M.W., Bernier, R., & Iverson, G.L. (2015). Prolonged activity restriction after concussion: Are we worsening outcomes? Clinical Pediatrics, 55(5) 443–451. doi:10.1177/0009922815589914 Google Scholar
Edmed, S.L., & Sullivan, K.A. (2015). Diagnostic terminology is not associated with contact-sport players’ expectations of outcome from mild traumatic brain injury. Brain Injury, 29(5), 623–632. doi:10.3109/02699052.2014.998709 Google Scholar
Gelman, A., & Rubin, D.B. (1992). Inference from iterative simulation using multiple sequences. Statistical Science, 7(4), 457–511.Google Scholar
Giza, C.C., & Hovda, D.A. (2001). The neurometabolic cascade of concussion. Journal of Athletic Training, 36(3), 228–235. doi:10.1227/NEU.0000000000000505 Google Scholar
Goffman, E. (1974). Frame analysis. New York: Harper & Row.Google Scholar
Gronwall, D. (1977). Paced auditory serial-addition task: A measure of recovery from concussion. Perceptual and Motor Skills, 44, 367–373.Google Scholar
Hoffman, S.J., & Justicz, V. (2016). Automatically quantifying the scientific quality and sensationalism of news records mentioning pandemics: Validating a maximum entropy machine-learning model. Journal of Clinical Epidemiology, 75, 1–9. doi:10.1016/j.jclinepi.2015.12.010 Google Scholar
Hou, R., Moss-Morris, R., Peveler, R., Mogg, K., Bradley, B.P., & Belli, A. (2012).When a minor head injury results in enduring symptoms: A prospective investigation of risk factors for postconcussional syndrome after mild traumatic brain injury. Journal of Neurology, Neurosurgery, & Psychiatry, 83 (2), 217–223. doi:10.1136/jnnp-2011-300767 Google Scholar
Institute of Medicine. (2004). Health literacy: A prescription to end confusion. Washington, DC: The National Academies Press. doi:10.17226/10883 Google Scholar
King, N.S., Crawford, S., Wenden, F.J., Moss, N.E.G., & 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(9), 587–592.Google Scholar
Kinkela, J.H. (2008). Diagnosis threat in mild traumatic brain injury (Unpublished doctoral dissertation). Ohio University, Athens, Ohio.Google Scholar
Kit, K., Mateer, C., Tuokko, H., & Spencer-Rodgers, J. (2014). Influence of negative stereotypes and beliefs on neuropsychological test performance in a traumatic brain injury population. Journal of the International Neuropsychological Society, 20(2), 157–167. doi:10.1017/S1355617713001264 Google Scholar
Klemm, C., Das, E., & Hartmann, T. (2014). Swine flu and hype: A systematic review of media dramatization of the H1N1 influenza pandemic. Journal of Risk Research, 19, 37–41. doi:10.1080/13669877.2014.923029 Google Scholar
Kruschke, J. (2015). Doing Bayesian Data Analysis: A tutorial with R, JAGS, and Stan (2nd ed.). Waltham, MA: Academic Press/Elsevier.Google Scholar
Konstantopoulos, S. (2011). Fixed effects and variance components estimation in three-level meta-analysis. Research Synthesis Methods, 2(1), 61–76. doi:10.1002/jrsm.35.Google Scholar
Kumar, S., Rao, S.L., Chandramouli, B.A., & Pillai, S. (2013). Reduced contribution of executive functions in impaired working memory performance in mild traumatic brain injury patients. Clinical Neurology and Neurosurgery, 115(8), 1326–1332. doi:10.1016/j.clineuro.2012.12.038 Google Scholar
Kutner, M., Greenberg, E., Jin, Y., & Paulsen, C. (2006). The Health Literacy of America’s Adults. Washington, DC: Institute of Education Sciences.Google Scholar
Lipton, R.B., Katz, M.J., Kuslansky, G., Sliwinski, M.J., Stewart, W.F., Verghese, J., Buschke, H. (2003). Screening for dementia by telephone using the Memory Impairment Screen. Journal of the American Geriatrics Society, 51(10), 1382–1390. doi:10.1046/j.1532-5415.2003.51455.x Google Scholar
Ozen, L.J. & Fernandes, M.A. (2011). Effects of “diagnosis threat” on cognitive and affective functioning long after mild head injury. Journal of the International Neuropsychological Society, 17, 219–229. doi:10.1017/S135561771000144X Google Scholar
Paniak, C., Reynolds, S., Phillips, K., Toller-Lobe, G., Melnyk, A., & Nagy, J. (2002). Patient complaints within one month of mild traumatic brain injury: A controlled study. Archives of Clinical Neuropsychology, 17(4), 319–334. doi:10.1016/S0887-6177(01)00115-9 Google Scholar
R Core Team. (2017). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. Retrieved from http://www.R-project.org/ Google Scholar
Rao, S.M., Leo, G.J., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis: Frequency, patterns, and prediction. Neurology, 41, 685–691.Google Scholar
Rao, S.M., Leo, G.J., Haughton, V.M., St. Aubin-Faubert, P., & Bernardin, L. (1989). Correlation of magnetic resonance imaging with neuropsychological testing in multiple sclerosis. Neurology, 39, 161–166.Google Scholar
Reuben, A., Sampson, P., Harris, A.R., Williams, H., & Yates, P. (2014). Postconcussion syndrome (PCS) in the emergency department: Predicting and pre-empting persistent symptoms following a mild traumatic brain injury. Emergency Medicine Journal, 31(1), 72–77. doi:10.1136/emermed-2012-201667 Google Scholar
Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3), 638–641. https://doi.org/10.1037/0033-2909.86.3.638 Google Scholar
Roth, R.S., & Spencer, R.J. (2013). Iatrogenic risk in the management of mild traumatic brain injury among combat veterans: A case illustration and commentary. International Journal of Physical Medicine & Rehabilitation, 01(01), 1–7. doi:10.4172/2329-9096.1000105 Google Scholar
Scheufele, D. (1999). Framing as a theory of media effects. Journal of Communication, 49(1), 103–122. doi:10.1111/j.1460-2466.1999.tb02784.x Google Scholar
Scheufele, D.A., & Tewksbury, D. (2007). Framing, agenda setting, and priming: The evolution of three media effects models. Journal of Communication, 57(1), 9–20.Google Scholar
Silverberg, N.D., & Iverson, G.L. (2011). Etiology of the post-concussion syndrome: physiogenesis and psychogenesis revisited. Neurorehabilitation, 29(4), 317–329. doi:10.3233/NRE-2011-0708 Google Scholar
Stan Development Team (2017). RStan: The R interface to Stan. R package version 2.3.1. Retrieved from http://mc-stan.org/ Google Scholar
Steele, C.M. (1997). A threat in the air. How stereotypes shape intellectual identity and performance. The American Psychologist, 52(6), 613–629. doi:10.1037/0003-066X.52.6.613 Google Scholar
Strauss, E., Sherman, E., & Spreen, O. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary (3rd ed.). New York: Oxford University Press.Google Scholar
Suhr, J., & Gunstad, J. (2002). “Diagnosis Threat”: The effect of negative expectations on cognitive performance in head injury. Journal of Clinical and Experimental Neuropsychology, 24(4), 448–457. doi:10.1076/jcen.24.4.448.1039 Google Scholar
Suhr, J., & Gunstad, J. (2005). Further exploration of the effect of “diagnosis threat” on cognitive performance in individuals with mild head injury. Journal of the International Neuropsychological Society,11(1), 23–29. doi:10.1017/S1355617705050010 Google Scholar
Trontel, H.G., Hall, S., Ashendorf, L., & O’Connor, M.K. (2013). Impact of diagnosis threat on academic self-efficacy in mild traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 35, 960–970. doi:10.1080/13803395.2013.844770 Google Scholar
Van Slooten, E., Friedman, D.B., & Tanner, A. (2013). Are we getting the health information we need from the mass media? An assessment of consumers’ perceptions of health and medical news. Journal of Consumer Health on the Internet, 17(1), 35–53. doi:10.1080/15398285.2013.756338 Google Scholar
Vanderploeg, R.D., Belanger, H.G., & Kaufmann, P.M. (2014). Nocebo effects and mild traumatic brain injury: Legal implications. Psychological Injury and Law, 7(3), 245–254. doi:10.1007/s12207-014-9201-3 Google Scholar
Waldron-Perrine, B., Tree, H.A., Spencer, R.J., Suhr, J., & Bieliauskas, L. (2015). Informational literature influences symptom expression following mild head injury: An analog study. Brain Injury, 29(9), 1–5. doi:10.3109/02699052.2015.1004742 Google Scholar
Weathers, F.W., Litz, B.T., Keane, T.M., Palmieri, P.A., Marx, B.P., & Schnurr, P.P. (2013). The PTSD Checklist for DSM-5 (PCL-5). Retrieved from http://ptsd.va.gov Google Scholar
Witthöft, M., & Rubin, G.J. (2013). Are media warnings about the adverse health effects of modern life self-fulfilling? An experimental study on idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF). Journal of Psychosomatic Research, 74(3), 206–212. doi:10.1016/j.jpsychores.2012.12.002 Google Scholar
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