Traumatic Brain Injury Screening Tools in Primary Care
Bibliographic record
Abstract
Traumatic brain injuries are a significant health concern, being responsible for over 52,000 deaths each year. Unfortunately, many traumatic brain injuries often go misdiagnosed or undiagnosed. Primary care providers are the principal and first source of medical contact for individuals, meaning that they are vital in the diagnosis of previous traumatic brain injuries in order to prevent future sequelae. There are currently several well-validated screening tools currently available for use by primary care providers. This study uses a self-reported survey to determine which of these tools are used by primary care nurse practitioners from a northern New England state and to compare the results to the suggestions made in current literature. The tools chosen by different primary care providers vary greatly, as do the indications used for initiation of traumatic brain injury screening. There were a total of 17 participants in the study, all of whom were at least masters level prepared nurse practitioners. The average number of years spent in practice was 11.7, with an average of 10.4 of those years in primary care. The most commonly used screening tool was the Mini Mental Status Exam, followed by the Montreal Cognitive Assessment and the CDC Acute Concussion Evaluation tool. Screening tools developed specifically for TBI assessment, such as the Ohio State University TBI ID Method and the Brief Traumatic Brain Injury Questionnaire were found to be seldom used (17% of total participants). Many primary care providers do not feel confident in their ability to diagnose such injuries, often due to lack of expertise in the area, which was reflected in the self-reported survey. As new screening tools become available, it is imperative that they are tested for validity, and then utilized in practice. Due to the complexity of diagnosing traumatic brain injuries, the most simple and accurate screening tools are often the ones preferred by providers. Moving forward, simple new screening tools need to be evaluated for effectiveness and ease of use. These tools should then be introduced to primary care practitioners, with suggestions as to how to best supplement them with other parts of an exam. Since TBIs are becoming an increasingly more common diagnosis in primary care, future advanced nursing evidence-based practice should focus on the recommended screening tools so as to better identify and guide treatment. Future research is needed to evaluate the extent to which part of an exam yield the most pertinent and accurate findings, as well as to compare the effectiveness of screening models utilized in civilian and military settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".