Evaluating Transcranial Direct Current Stimulation as an Adjunct to In-Patient Physiotherapy in Paediatric Acquired Brain Injury: A Randomized Feasibility Trial
Bibliographic record
Abstract
Purpose: Evaluate the feasibility of transcranial direct current stimulation (tDCS) as an adjunct to in-patient physiotherapy for children and youth with acquired brain injury (ABI). Method: This randomized feasibility trial allocated children (5-18 years of age with moderate to severe ABI) to receive either active or sham anodal tDCS immediately prior to 16 of their existing in-patient physiotherapy sessions. Participants, physiotherapists, assessors, and primary investigators were blinded to treatment allocation. Eligibility, recruitment, retention, tolerance, and preliminary treatment outcomes were evaluated against a priori feasibility targets. Results: Of 232 children admitted over 21 months, 6 were eligible (2.6%) and 4 were recruited (66.7%). One participant completed the entire study protocol, two were withdrawn for unrelated changes in medical stability, and one could not commence the study due to COVID-19 restrictions. Participants completed all tDCS sessions that were started with the primary transient side effect being sub-electrode itchiness. Conclusions: While the study was infeasible from eligibility and retention perspectives, study procedures (e.g., assessment, treatment, side effect tracking, physiotherapy documentation) were viable and should be applied to future paediatric tDCS studies.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".