“Take-home” functional electrical stimulation for depression: protocol for a prototype development and proof of concept randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: One-third of patients with major depressive disorder (MDD) will not achieve a clinically meaningful response to available conventional treatments. More effective neurostimulation treatments are difficult to access and are associated with high hospital delivery costs. Patients would benefit from more efficacious and well-tolerated home-based neurostimulation treatments, which could be self-administered at a frequency required to treat MDD, maintain response, and reduce relapse. A potential novel intervention for MDD is bilateral functional electrical stimulation (FES) of the facial muscles. The portable FES stimulator delivers electrical current to excitable tissues and is suitable for home-based use. Based on the preliminary work demonstrating the feasibility of FES for MDD, the proposed study will develop a viable prototype for a "take-home" FES device and perform a proof-of-concept feasibility trial for participants with MDD. METHODS: This is a single-site, pilot, double-blind, randomized, sham-controlled clinical trial, where 20 participants will receive 20 sessions of FES over 4 weeks. The trial will evaluate the feasibility, tolerability, and safety of home-based FES for MDD. We will also collect data on the preliminary therapeutic effects of FES on depressive symptoms and associated anxiety, quality of life, and sleep. Eligible participants will have three on-site visits including one mask development visit, one mask delivery visit, and one follow-up visit at the end of the study. They will also attend 25 online visits including a screening visit, a baseline visit, 20 days of FES treatment (sham or active), and three post-stimulation follow-up visits. DISCUSSION: Data obtained from this trial will be used to optimize the home-based FES prototype and design a follow-up, multi-site, large-scale randomized control trial to assess the effectiveness of take-home FES. The existing evidence suggests that FES of the facial muscles can reduce MDD symptoms by enhancing positive facial feedback and altering the interoceptive bias associated with MDD, but its exact mechanism of action is still under debate. Additional trials with neuroimaging outcomes are needed to elucidate the mechanism of action of FES and the corresponding changes in the central nervous system. TRIAL REGISTRATION: This trial has been registered at the National Library of Medicine, National Center for Biotechnology Information (ClinicalTrials.gov: NCT06261177 . Registered on January 4, 2024).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".