Algorithm for Symptom Attribution and Classification Following Possible Mild Traumatic Brain Injury

Objective: To present a heuristic model of a symptom attribution and classification algorithm (SACA) for mild traumatic brain injury (mTBI). Setting: VA Polytrauma sites. Participants: 422 Veterans. Design: Cross-sectional. Main Measures: SACA, Comprehensive TBI Evaluation (CTBIE), Structured TBI Diagnostic Interview, Minnesota Multiphasic Personality Inventory (MMPI-2-RF), Letter Memory Test, Validity-10. Results: SACA and CTBIE diagnoses differ significantly (P < .01). The CTBIE, compared with SACA, attributes 16% to 500% more symptoms to mTBI, behavioral health (BH), mTBI + BH and symptom resolution. Altering SACA criteria indicate that (1) CTBIE determination of cognitive impairment yields 27% to 110% more mTBI, mTBI + BH and symptom resolution diagnoses, (2) ignoring timing of symptom onset yields 32% to 76% more mTBI, mTBI + BH and Other Condition diagnoses, (3) Proportion of sample having questionably valid profiles using structured TBI diagnostic interview and MMPI-2-RF and Letter Memory Test is 26% whereas with CTBIE item number 23 and Validity-10 is 6% to 26%, (4) MMPI-2-RF F-scale is the only measure identifying Veterans with posttraumatic amnesia for more than 24 hours as having questionably valid profiles. Conclusions: Symptom attribution-based diagnoses differ when using status quo versus the SACA. The MMPI-2-RF F-scale, compared with the Validity-10 and LetterMemory Test, may be more precise in identifying questionably valid profiles for mTBI + BH. The SACA provides a framework to inform clinical practice, resource allocation, and future research.