Objectives: Recovery from traumatic brain injury (TBI) is extremely difficult to predict, with TBI severity usually demonstrating weak predictive validity for functional or other outcomes. A possible explanation may lie in the statistical phenomenon called suppression, according to which a third variable masks the true association between predictor and outcome, making it appear weaker than it actually is. Age at injury is a strong candidate as a suppressor because of its well-established main and moderating effects on TBI outcomes. We tested age at injury as a possible suppressor in the predictive chain of effects between TBI severity and functional disability, up to 10 years post-TBI.
Setting: Follow-up interviews were conducted during telephone interviews.
Participants: We used data from the 2020 NDILRR Model Systems National Dataset for 4 successive follow-up interviews: year 1 (n = 10,734), year 2 (n = 9174), year 5 (n = 6,201), and year 10 (n = 3027).
Design: Successive cross-sectional multiple regression analyses.
Main measures: Injury severity was operationalized using a categorical variable representing duration of posttrauma amnesia. The Glasgow Outcomes Scale-Extended (GOS-E) operationally defined functioning. Sociodemographic characteristics having significant bivariate correlations with GOS-E were included.
Results: Entry of age at injury into the regression models significantly increases the association between TBI severity and functioning up to 10 years post-TBI.
Conclusions: Age at injury is a suppressor variable, masking the true effect of injury severity on functional outcomes. Identifying the mediators of this suppression effect is an important direction for TBI rehabilitation research.
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