A remote health intervention to reduce impairing post-concussional mild-to-moderate symptoms in adults (GAIN Lite): Study protocol for a parallel group randomised trial
Bibliographic record
Abstract
Abstract Background: Mild traumatic brain injury, commonly known as concussion, has been estimated to be around 600 per 100.000 yearly in Denmark, and 30-50 million new cases worldwide. Although complete resolution normally occurs within a few weeks, up to a third develop persistent post-concussion symptoms (PPCS) beyond 3 months. However, evidence for effective treatment strategies is scarce. The objective of this study is to evaluate the efficacy of the novel intervention GAIN Lite added to enhanced usual care (EUC) for adults with mild-to-moderate PPCS compared to EUC only. Methods: An open-label, parallel-group, two-arm randomized controlled superiority trial (RCT) with 1:1 allocation ratio. Participants will be randomly assigned to either: 1) EUC or; 2) GAIN Lite added to EUC. GAIN Lite is characterized as a complex intervention and has been developed, feasibility-tested, and process evaluated before effect evaluation in the RCT. Sixty-six participants will be recruited to each group. Potential participants will be identified through the hospital's Business Intelligence portal of the Central Denmark Region or referred by general practitioners within 2-4 months post-concussion. Primary outcomes are mean changes in PPCS and limitations in daily life from baseline to 24 weeks after baseline Discussion: GAIN Lite is a low-intensity intervention for adults with mild-to-moderate PPCS. Offering a remote intervention may improve access to rehabilitation and prevent chronification for individuals with mild-to-moderate PPCS. Moreover, GAIN Lite will facilitate access to healthcare, especially for those with transportation barriers. Overall, GAIN Lite may provide an accessible, flexible, and convenient way to receive treatment based on sound theories and previous evidence of effective interventions for adults with mild-to-moderate PPCS. Trial Registration: URL: ClinicalTrials.gov Identifier:NCT05233475. Registered on 10th of February 2022.
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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 | 0.020 | 0.022 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.075 | 0.012 |
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".