Psycho-affective And Cognitive Outcomes In Slow To Recover Concussed Athletes
Bibliographic record
Abstract
PURPOSE: Although the majority of concussed athletes are believed to recover within 7 to 10 days following the injury, up to 20% of injured athletes will experience persisting symptoms (McCrory, 2013). However, little is known about the psycho-affective and cognitive outcomes of slow to recover athletes (SRA) compared to asymptomatic concussed athletes (ACA). Compare the psycho-affective and cognitive health in SRA, ACA and athletes without a history of concussion (NHC). We hypothesised that SRA would significantly differ from ACA and NHC for both emotional symptoms and cognitive performance. METHODS: Twenty SRA were match on age, gender, time since injury (m = 49.3 ± 40.0 days) and history of concussion (m = 2.2 ± 1.3 with twenty ACA and on age and gender with NHC. All participants completed the Beck’s Depression Inventory-II (BDI-II), which measures depression, and the Profile of Mood State (POMS), which measures aspects of mood disturbance (Tension-Anxiety, Depression-Dejection, Anger-Hostility, Fatigue-Inertia, Vigor-Activity and Confusion-Bewilderment and total mood disturbance). Participants also completed a 2-back to task to evaluate working memory. RESULTS: SRA exhibited greater depressive symptoms on the BDI-II relative to ACA and NHC (p = <0.05). SRA also differed from ACA and NHC in terms of Depression-Dejection, Anger-Hostility, Vigor-Activity, Confusion-Bewilderment, and total mood disturbance on the POMS (p = < 0.05). Analysis of the 2-back revealed that SRA exhibited slower RT and lower ACC relative to NHC (p = < 0.05), but not ACA. ACA did not different from NHC on any measure. CONCLUSIONS: These results suggest that athletes with persistent symptoms exhibit worse psycho-affective status relative to asymptomatic athletes with and history of concussion and poorer cognitive performance relative to control athletes. Thus, psycho-affective status and cognitive performance might be used to track recovery and help clinical management of athletes with persistent symptoms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".