A Pilot Feasibility Study of a Home Tablet-Based Neurorehabilitation Program and Serial Brain Vital Sign Monitoring for Survivors of Pediatric Cerebral Malaria
Bibliographic record
Abstract
Lasting sequelae are identified in 50% of child survivors of cerebral malaria (CM). Rehabilitation options in malaria-endemic regions are scarce and largely focused on physical deficits, leaving children without support for cognitive recovery. Effective and accessible interventions are vital for improving outcomes. Furthermore, the assessment of brain function and recovery after CM is dependent on behavior-based tests that are time-consuming and require substantial training to administer. Objective, easy-to-use alternatives may be impactful. Children aged 3-12 years who had survived CM were recruited. Participants underwent a 6-month in-home, tablet-based neurorehabilitation program called Dino Island (DI). Participants also underwent serial assessments of brain health that were conducted by measuring event-related potentials (ERPs) using the Brain Vital Signs system. The feasibility, fidelity, acceptability, appropriateness, and affordability of the interventions were evaluated through interviews with the study nurses and the participants' families. Both programs were feasible and easy to implement. Acceptability was demonstrated by low attrition rates (5%) and positive family ratings (100%). Appropriateness for DI was confirmed by parent reports of positive behavioral changes in their children (60%). For Brain Vital Signs, appropriateness was confirmed by adequate data acquisition for most participants. Finally, positive indicators of affordability from a healthcare perspective were identified. Neurorehabilitation using a home tablet-based program and objective brain health assessment using ERPs was feasible, well accepted, and appropriate in child CM survivors in sub-Saharan Africa. Further development and research into the program's ability to improve and measure cognitive recovery is justified.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".