Cranial Nerve Noninvasive Neuromodulation in Adults With Neurological Conditions: Protocol for a Scoping Review (Preprint)
Bibliographic record
Abstract
BACKGROUND Cranial nerve noninvasive neuromodulation (CN-NINM) via translingual nerve stimulation (TLNS) is a promising new intervention combined with neurological rehabilitation to improve outcomes for persons with neurological conditions. A portable neuromodulation stimulation (PoNS) device rests on the tongue and stimulates cranial nerves V and VII (trigeminal and facial nerves, respectively). Emerging evidence suggests that CN-NINM using the PoNS device, combined with targeted physical therapy, improves balance and gait outcomes but has not yet been comprehensively reviewed. OBJECTIVE This review will describe CN-NINM via TLNS and its applications, effects, and implications for rehabilitation science in adult populations with neurological conditions. We will identify how CN-NINM via TLNS is currently being incorporated into neurological rehabilitation and identify gaps in evidence with respect to this novel technology. METHODS Joanna Briggs Institute methodology will be used to conduct this scoping review. Electronic databases MEDLINE, AMED, CINAHL, Embase, and Web of Science will be searched, as well as gray literature databases ProQuest, DuckDuckGo, and Google. Studies published in English and French between 2000 and 2021 will be included. Two reviewers will independently screen all titles and abstracts and full-text papers that meet the inclusion criteria. Data will be extracted and collated in a table to synthesize the results. Extracted data will be reported in a comprehensive summary. RESULTS The final manuscript is intended for submission to an indexed journal in September 2021. CONCLUSIONS This scoping review will be the first, to our knowledge, to address the current evidence on CN-NINM. The results will inform the use of CN-NINM in neurological rehabilitation and the development of recommendations for future research. CLINICALTRIAL Open Science Framework 10.17605/OSF.IO/XZQFM; https://osf.io/xzqfm INTERNATIONAL REGISTERED REPORT PRR1-10.2196/29965
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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 | 0.058 | 0.064 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.087 | 0.013 |
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".