School-Based Neurofeedback Training for Sustained Attention
Bibliographic record
Abstract
OBJECTIVE: To determine whether in situ neurofeedback training can be used as a tool to build sustained attention in the general student population and whether gains in attention translate to more effective work habits and learning skills. METHOD: Students participated in attention training game-based neurofeedback in situ for a period of 35 sessions of 25 min each. The study was built as a one-group pretest-posttest quasi-experimental design. RESULTS: This study supports that classroom-based neurofeedback may be an effective tool to build sustained attention and translate these gains into observable work habits and learning behaviors including planning and organization. CONCLUSION: Neurofeedback has shown specificity in the treatment of Attention Deficit Hyperactivity Disorder. Published research has not, however, focused on its efficacy in developing attentional capacities in the general population. The promising results of this exploratory investigation warrant further applied research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".