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Record W7135731848

A brief physiotherapist-led behaviour-change intervention to facilitate walking in older people with peripheral arterial disease:protocol for a randomised controlled trial

2018· article· en· W7135731848 on OpenAlexaff
Melissa Galea Holmes, John Weinman, Janet Lesley Peacock, Saskia Eddy, Bijan Moderai, Sanjay Patel, Graham Fisher, Catherine Mary; id_orcid 0000-0002-8580-6622 Sackley, Lindsay Mary; id_orcid 0000-0002-2190-8590 Bearne

Bibliographic record

VenueResearch Portal (King's College London) · 2018
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsInstitute of Population and Public Health
Fundersnot available
KeywordsIntermittent claudicationRandomized controlled trialIntervention (counseling)Logistic regressionQuality of life (healthcare)Motivational interviewingOlder peopleClaudication
DOInot available

Abstract

fetched live from OpenAlex

Background: Walking is a recommended but underused treatment for intermittent claudication (IC) caused by peripheral arterial disease. Following feasibility evaluation, the efficacy of a novel physiotherapist-led intervention targeting walking in people with IC will be evaluated. Methods: A phase II, multicentre, parallel, two-arm, single-blind, randomised controlled superiority trial will allocate (1:1, stratified by site) 192 people with IC to receive MOtivating Structured walking in Intermittent Claudication (MOSAIC) or usual NHS care. MOSAIC includes two 60-min individual face-to-face sessions and two 20-minute telephone boosters delivered over three months by a physiotherapist trained in motivational interviewing and behaviour-change techniques. The primary outcome is walking ability (6 Minute Walking Distance [6MWD]) 3 months post-randomisation. Secondary outcomes include, walking ability, activities of daily living, and quality of life (3 and 6-months). A qualitative sub-study (purposive sample of ~30 participants,10 physiotherapists) will explore in-depth experiences. A process evaluation of MOSAIC implementation, mechanisms, and unexpected pathways and consequences will be conducted. Results: Intention-to-treat analysis using multiple regression (baseline 6MWD value, stratification factor and centre as covariates) will evaluate the primary outcome. Mean differences (95% Confidence Intervals) between groups will be reported. Other continuous outcomes will be evaluated similarly. Logistic regression will be used to analyse binary outcomes. Interviews with up to 30 participants and physiotherapists will be analysed thematically. Discussion: MOSAIC is designed to support walking self-management in people with IC who frequently receive only simple walking advice, which is ineffective. Conclusion: If efficacious, MOSAIC will enable people with IC to improve their mobility, daily activities, independence and quality of life.

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)0.036
metaresearch head score (Gemma)0.031
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 score0.096
Threshold uncertainty score0.322

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.031
Meta-epidemiology (narrow)0.0060.003
Meta-epidemiology (broad)0.0120.006
Bibliometrics0.0030.004
Science and technology studies0.0040.003
Scholarly communication0.0040.003
Open science0.0040.003
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0960.017

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 head0.058
GPT teacher head0.377
Teacher spread0.319 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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