Perceptual Cognitive Training Does Not Improve Clinical Outcomes at 4 and 12 Weeks Following Concussion in Children and Adolescents: A Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: To determine whether a perceptual-cognitive training program using 3D-multiple object tracking (3D-MOT) can improve symptoms following acute pediatric concussion. SETTING: Research laboratory within a pediatric trauma center. PARTICIPANTS: Children and adolescents (n = 62, age= 13.27 ± 2.50) with diagnosed concussion. DESIGN: Randomized controlled trial. Children were randomized into either 3D-MOT, 2048 game, or standard care-only groups. Participants and parents completed the Post-Concussion Symptom Inventory (PCSI) at baseline, 4, 8, and 12 weeks postinjury. Intervention participants completed either the 3D-MOT protocol or the 2048 game at 6 sessions between the baseline and 4-week assessment. MAIN MEASURES: A 3 (group) × 10 (time) mixed-model analysis of variance evaluated PCSI total scores. The rate of persistent postconcussive symptom (PPCS) was evaluated at 4 weeks using χ2 analysis. RESULTS: Symptoms decreased throughout the study using both child-reported (F(9,374) = 22.03, P < .001) and parent-reported scores (F(9,370) = 28.06, P < .001). Twenty-four (44.4%) children met the study definition for PPCS using the child-reported PCSI, while 20 (37.7%) children had PPCS using parent reports. The intervention did not significantly affect symptom resolution or PPCS rates. CONCLUSION: There is no benefit to prescribing 3D-MOT training for acute rehabilitation in pediatric patients with concussion and clinicians should instead focus on more effective programs.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".