Active Brain & Nervous System

Better Balance-NMD: Developing pragmatic and innovative interventions to optimise physical function in neuromuscular diseases and related conditions

In plain English

AI plain-English summary

People with neuromuscular diseases such as Charcot-Marie-Tooth disease and CANVAS syndrome fall frequently, often with devastating injuries, yet no evidence-based balance training exists for them. This matters because neuromuscular diseases are rare and heterogeneous—each condition affects balance differently, so a one-size-fits-all rehabilitation programme cannot work. Current clinical guidance offers little more than generic fall-prevention advice, leaving patients without targeted, practical help. The Better Balance-NMD project will build a five-stage research pipeline to develop, test, and deliver disease-specific balance interventions. For CANVAS, researchers will first map what drives poor balance, then co-design a home-based training programme and test it for feasibility. For Charcot-Marie-Tooth disease, the team will skip straight to creating digital training content and run a phase-3 trial comparing the programme against usual care. If successful, the project will produce pragmatic, evidence-based balance interventions that patients can use at home, tailored to their specific condition. The framework will also allow other neuromuscular diseases to plug into the same pipeline, accelerating development of rehabilitation tools for a neglected group of patients.

View original technical description
The primary purpose of Better Balance-NMD is to develop an evidence informed framework as a research pipeline with five stages of development of balance rehabilitation for people living with Neuromuscular Diseases (NMDs). Background:?The umbrella term NMD describes a group of rare conditions affecting the peripheral neuromuscular structures. Falls are commonly experienced with potentially devastating consequences for people with NMD. Rare diseases are challenged by a lack of high-quality, evidence-based interventions, specific to each disease. NMDs are heterogenous so understanding contributors to poor balance should guide targeting of rehabilitation interventions, that can then be tested and pragmatically delivered. The Better Balance pipeline will allow common learning across conditions to inform the framework, while still allowing disease-specific refinements. Aims and objectives: Aim 1: Development of the Better Balance-NMD pipeline: A synthesis of literature and observational study data will investigate contributors to balance impairment to inform a prototype. This will be tested for feasibility, refined and a delivery platform will be co-produced through the POD-NMD website https://www.pod-nmd.org/ for testing in a phase-3 trial. Aim 2:?? Expansion of the Neuromuscular Rehabilitation Research Group: Mentor research group colleagues to acquire their own funding and develop interventions using the Better Balance pipeline model. Better Balance-NMD will centre on key stages in the pipeline, with two condition specific study streams: ?Better Balance-CANVAS (for Cerebellar Ataxia Neuropathy Vestibular Areflexia Syndrome) and Better Balance-CMT (for Charcot-Marie-Tooth disease). They will step onto and off the pipeline at different points: Stage 1: Synthesis of literature and observational data to describe a model of balance impairment for the specific NMD. Stage 2: Co-produce a prototype Better Balance-NMD training programme to address contributors to balance impairment. Stage 3: Proof of concept testing of the Better Balance-NMD training programme to explore feasibility, acceptability, evidence of effect, fidelity, and outcome measures. Stage 4: Co-production of the Better Balance-NMD section of the POD-NMD website, with testing and refinement. Stage 5: Phase 3 hybrid trial of Better Balance-NMD training programme to investigate efficacy and implementation. Methods: ?Better Balance-CANVAS will start by developing a model of balance impairment through a scoping review of literature and an observational study (Stage 1). This data will underpin the intervention design (Stage 2) drawing on rehabilitation interventions targeting contributors to instability. This will be tested through a proof-of-concept evaluation to ascertain the feasibility of supported training delivered at home (Stage 3). Better Balance-CMT will build on the current body of observational data, and my work prior to the fellowship. Stage 4 will produce the digital content with people living with CMT, the POD-NMD developers and experience-based co-design experts. Stage 5 will be a phase 3, hybrid trial of efficacy and implementation. Timelines for delivery:?This will be a five-year fellowship with completion of Better Balance-CANVAS in year 4, and Better Balance-CMT in year 5. Anticipated impact and dissemination:?Once established Better Balance-NMD will produce pragmatic, effective, and disease specific balance interventions in CMT, CANVAS and other NMDs. National and international patient advocacy groups and neuromuscular networks will drive dissemination.

View the original record at the funder ↗

Related Research

Grants with similar aims, by meaning.

The co-creation of personalised, multifaceted balance training delivered alongside pulmonary rehabilitation to reduce falls risk for people with Chronic Obstructive Pulmonary Disease
ADAPT NMD: A hybrid II study of the feasibility and implementation of a self-management programme for people with neuromuscular diseases
A multi-centre randomised controlled trial to assess the effectiveness and cost effectiveness of a home-based self-management standing frame programme in people with progressive MS
Evaluating the benefits of community based aerobic training on the physical health and well-being of people with neuromuscular diseases: a pilot study
Maintaining function and participation through whole-system, tailored physical activity for people living with frailty and multiple cardiorenal metabolic conditions (the PERSONAL-AGILITY study).

Original classification

None

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.