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Record W3171894649 · doi:10.2196/29965

Cranial Nerve Noninvasive Neuromodulation in Adults With Neurological Conditions: Protocol for a Scoping Review

2021· review· en· W3171894649 on OpenAlexafffundvenue
Keaton Boughen, Tyler Neil, Shayan Dullemond, Kevin Lutowicz, Ahmed Bilgasem, Tyler Hastings, Dina Brooks, Julie Vaughan‐Graham

Bibliographic record

VenueJMIR Research Protocols · 2021
Typereview
Languageen
FieldNeuroscience
TopicVagus Nerve Stimulation Research
Canadian institutionsUniversity of TorontoMcMaster University
FundersMcMaster University
KeywordsCINAHLNeuromodulationMedicineMEDLINEPhysical medicine and rehabilitationRehabilitationPhysical therapyPsychological interventionStimulationNursing

Abstract

fetched live from OpenAlex

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. TRIAL REGISTRATION: Open Science Framework 10.17605/OSF.IO/XZQFM; https://osf.io/xzqfm. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/29965.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.357
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.630
GPT teacher head0.659
Teacher spread0.028 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreProtocol

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".

Quick stats

Citations5
Published2021
Admission routes3
Has abstractyes

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