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Record W4408241794 · doi:10.1186/s40814-025-01608-6

Co-designed neck exercise (EPIC-Neck) vs usual exercise care for people with chronic non-specific neck pain: protocol for a randomised feasibility study with process evaluation

2025· article· en· W4408241794 on OpenAlexaff
Jonathan Price, Alison Rushton, Natalie Ives, Kate Jolly, Priya Parmar, Colin Greaves

Bibliographic record

VenuePilot and Feasibility Studies · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsWestern University
FundersNational Institute for Health and Care Research
KeywordsMedicineNeck painPhysical therapyProtocol (science)EPICAlternative medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical guidelines recommend that people with chronic non-specific neck pain self-manage symptoms with physiotherapy-led exercise. However, current exercise strategies have modest short-term effects, engagement is poor, and 48% of people continue to experience long-term and recurrent pain. Updated exercise strategies co-produced using complex intervention development frameworks are required that consider the behavioural, psychological, environmental, and technical aspects of exercise prescription and patient adherence to optimise symptom outcomes, long-term engagement, and self-management. This study tests the feasibility and acceptability of the EPIC-Neck programme ("Exercise Prescription Improved through Co-design") which is grounded in evidence and theory and was co-produced using intervention mapping principles. The aim of the EPIC-Neck programme is to optimise the short-term outcomes of and long-term engagement with neck exercise. METHODS: This is a randomised feasibility study with process evaluation to assess the feasibility and acceptability of the EPIC-Neck programme and inform the design of a large-scale definitive trial evaluating the clinical and cost-effectiveness of the EPIC-Neck programme. A multicentre two-arm randomised controlled feasibility study aiming to recruit 45 adults with chronic non-specific neck pain will be conducted in UK NHS musculoskeletal physiotherapy departments. Recruitment will be from waiting lists and clinic advertisements. Participants will be individually randomised in 2:1 ratio to either the EPIC-Neck programme (n = 30) or usual exercise care (n = 15). The primary feasibility objective is to determine whether to continue to a large-scale definitive trial by evaluating delivery fidelity, acceptability, contamination, and rates of recruitment and retention (outcome completion at follow-up). Other feasibility objectives are to evaluate safety, define usual exercise care, refine the EPIC-Neck programme and training, and explore the demographics of people who do and do not enrol onto the study. Outcomes will be assessed by questionnaires at baseline and at 3- and 6-month post-randomisation, appointment audio-recordings, and one-to-one semi-structured interviews with participants receiving the EPIC-Neck programme (n = 12-15) and physiotherapists. DISCUSSION: This feasibility study will provide evidence of the feasibility and acceptability of the EPIC-Neck programme and guide the development of a definitive randomised controlled trial evaluating its clinical and cost-effectiveness within the NHS. TRIAL REGISTRATIONS: ISRCTN81746901.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.057
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.071
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0570.044
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0090.007
Bibliometrics0.0040.004
Science and technology studies0.0040.005
Scholarly communication0.0040.004
Open science0.0050.005
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0710.014

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 head0.082
GPT teacher head0.412
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations1
Published2025
Admission routes1
Has abstractyes

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