Effectiveness of Game-Based Training of Selective Voluntary Motor Control in Children With Upper Motor Neuron Lesions: Randomized Multiple Baseline Design Study
Bibliographic record
Abstract
BACKGROUND: Selective voluntary motor control (SVMC) is the ability to control joint movements independently. Impairments in SVMC can affect functional activities, but only a few interventions directly target SVMC. Therefore, we developed a game-based intervention for children with upper motor neuron lesions to improve SVMC. The intervention trained selective activation of a muscle or joint movement while providing immediate feedback about involuntarily occurring muscle activations or movements in another joint. The intervention was provided in a playful manner with a custom-made game environment and a technology-based interface to capture muscle activation or joint movements. OBJECTIVE: This study aimed to investigate the effectiveness of this game-based intervention and explore treatment response-related factors in children with impaired SVMC undergoing inpatient neurorehabilitation. METHODS: We conducted a single-case research study with a randomized, nonconcurrent, multiple baseline design. The study consisted of a random-length baseline phase where no SVMC-specific intervention was provided and an intervention phase with additional SVMC training. Concurrently in both phases, children attended their individual multimodal rehabilitation program at our clinic, Swiss Children's Rehab. During the intervention phase, participants completed ten 45-minute sessions with our game-based SVMC training. SVMC was measured repeatedly throughout both phases and at the 3-month follow-up with a short custom-made assessment. RESULTS: Eighteen children with reduced SVMC from upper motor neuron lesions participated in the study. The mean age of the children was 12.7 (SD 2.9) years, and they mostly had spastic cerebral palsy. A linear mixed-effects model revealed a significant trend (P<.001) for improved SVMC already in the baseline phase. This trend did not change significantly (P=.15) when the game-based SVMC training was introduced in the intervention phase, suggesting no additional improvements due to the SVMC training. Although we could not find an overall treatment effect, we could explain 89.4% of the total random variation of the treatment effect by patient and therapy characteristics. Children with spasticity in the trained movement (20.1%), and those who trained the more affected side (23.5%) benefited most from the intervention. At the 3-month follow-up, SVMC had deteriorated compared to the end of the intervention but was still better than at the beginning of the study. CONCLUSIONS: The regular concomitant rehabilitation program already yielded improvements in SVMC, while the game-based SVMC training showed no additional effects. Although the intervention did not show a group effect, we could identify patient and therapy characteristics that determine who is likely to profit from the intervention. TRIAL REGISTRATION: German Clinical Trials Register DRKS00025184; https://tinyurl.com/msnkek9b.
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 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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".