The Functional Assessment of Balance in Concussion (FAB-C) Battery
Bibliographic record
Abstract
BACKGROUND: There is no clinical tool that assesses multiple components of postural control potentially impacted by sport-related concussion (SRC). OBJECTIVE: To develop and assess the feasibility and construct validity of the Functional Assessment of Balance in Concussion (FAB-C) battery. STUDY DESIGN: Cross-sectional study. METHODS: Tests for inclusion in the FAB-C battery were identified through a search of the literature. The feasibility and construct validity of the battery was assessed with a convenience sample of active individuals (13-24 years) with and without a SRC. Feasibility outcomes included battery completion (yes/no), number of adverse events, time to administer (minutes) and cost of the battery (Canadian Dollars). Construct validity was assessed by examining correlations between tests included in the battery, and describing differences [mean (standard deviation), median (range) or proportion] in outcomes between uninjured participants and participants with SRC. RESULTS: Seven tests were included in the FAB-C battery. All 40 uninjured participants [12 female; median age 17 years] completed the FAB-C assessment compared to 86% of seven participants with SRC [1 female; median age 17]. No participants demonstrated adverse effects. The median administration time of the battery was 49 minutes (range 44-60). The cost of the battery was low (~$100 Canadian Dollars). Limited correlations (r<0.7) between tests in the battery were observed. A greater percentage of uninjured participants (52% to 82%) passed individual tests in the battery compared to participants with SRC (17% to 66%). CONCLUSION: Although promising, the FAB-C battery requires further evaluation before adoption for widespread clinical use. LEVEL OF EVIDENCE: Level 3b.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".