Neuromuscular Electrical Stimulation to Maximize Hip Abductor Strength and Reduce Fall Risk in Older Veterans: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Nearly half of all veterans are 65 years and older, and they have a higher prevalence of functional disabilities compared to the nonveteran population. Balance impairments resulting in injurious falls are a leading cause of morbidity and mortality in older adults. Instability or fear of falling can significantly reduce physical activity and social participation, even in the absence of falls. Dysmobility is a leading factor in long-care admissions, and therefore, maintenance of mobility throughout aging is crucial. Recent evidence indicates lower extremity muscle weakness as a key risk factor for falls, with lower limb muscle strength and quality being critical for balance recovery. The primary hip abductors, the gluteus maximus, medius, and minimus, are particularly essential for balance recovery. OBJECTIVE: This study aims to test the hypothesis that adding neuromuscular electrical stimulation (NMES) to a multimodality balance intervention (MMBI) will yield greater reductions in fall risk and improvements in muscle and mobility function compared with MMBI alone. METHODS: This randomized controlled trial will enroll 80 veterans aged 55 years and older at risk for falls (defined by a four-square step test [FSST] time >12 seconds, history of falls, or fear of falling). Participants will be randomized to receive either NMES + MMBI or MMBI alone. The 12-week outpatient center-based intervention will include 3 sessions per week, focusing on hip abductor strength, balance, and mobility. Assessments will occur at baseline, postintervention, and at 6- and 12-month follow-ups. Primary outcomes include fall risk and dynamic balance, measured by FSST and hip abductor strength using a Biodex dynamometer. Secondary outcomes will examine muscle composition through computed tomography (CT) scans and assess gait variability parameters. RESULTS: This study was funded on January 1, 2022, with a data collection period from April 1, 2022, to December 31, 2026. As of March 2025, we have screened 100 potential participants and excluded 38. Out of the 61 participants enrolled to date, 21 have completed the 12-month follow-up, 32 have completed the 6-month follow-up, and 41 have completed the posttesting. A total of 4 participants are currently in the intervention phase; 1 has just completed the baseline testing, while 15 have been dropped from the study. CONCLUSIONS: This trial will be the first large, randomized controlled trial to evaluate NMES as an adjunct to an MMBI for fall prevention in older veterans. If successful, NMES combined with hip abductor strengthening and balance training could provide a low-cost, scalable solution to reduce falls, improve balance and mobility, and decrease health care costs related to falls in older adults. This study will address a critical gap in knowledge about the effectiveness of NMES in enhancing rehabilitation outcomes for fall prevention. TRIAL REGISTRATION: ClinicalTrials.gov NCT04969094; https://clinicaltrials.gov/study/NCT04969094. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/68082.
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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 | 0.024 | 0.027 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.074 | 0.010 |
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".