Running and Thinking: Unmasking the Lingering Effects of Sports Concussions Through Complex Dual-Task Testing
Bibliographic record
Abstract
Objective: This study investigated gait and cognitive dual-task costs under a dual-task paradigm that was more challenging than the traditional tasks used in research. Methods: A total of 43 18–25-year-old male and female student athletes were recruited (20 asymptomatic concussed athletes who suffered at least one concussion 2.79–7.92 months before testing, 23 never concussed). Athletes performed a complex rapid decision-making and executive function computerized task while walking continuously and maintaining a predetermined speed on a non-motorized treadmill (6.5 km/h). The outcome measures were gait and cognitive dual-task costs. Results: Repeated-measures ANOVAs were conducted to evaluate group differences. Pearson correlations were conducted to evaluate the association between dual-task costs and concussion injury variables. The results showed that both groups experienced greater difficulty with dual-task performance related to gait, whereas only the concussion group exhibited poorer cognitive performance under the dual-task condition (both not significant). The significant correlation between time since injury and gait dual-task cost (r = −0.72, p < 0.001) indicated that athletes with a more recent concussion increased their gait speed whilst athletes with an older concussion reduced their gait speed during the dual-task. Moreover, the cognitive dual-task cost was significantly correlated to symptom recovery (r = 0.461, p = 0.047), suggesting that a longer recovery time from concussion is associated with an increased dual-task cost. Conclusions: While dual-task gait alterations were common to both groups, only individuals with a history of concussion showed specific cognitive impairments under dual-task conditions. The observed associations between dual-task costs and both time since injury and symptom recovery underscore the potential of complex dual-task assessments to provide nuanced insights into post-concussion recovery trajectories and to detect subtle, lingering deficits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".