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Record W3213547454

TREATMENT FIDELITY IN THE GAIT REHABILITATION IN EARLY RHEUMATOID ARTHRITIS TRIAL (GREAT) FEASIBILITY STUDY

2020· article· en· W3213547454 on OpenAlexaff
Emma Godfrey, Mandeep Sekhon, Gordon Hendry, Nadine E. Foster, Samantha Hider, Marike van der Leeden, Helen Mason, Alex McConnachie, Iain B. McInnes, Aimie Patience, Catherine Sackley, Martijn Steultjens, Anita Williams, James Woodburn, Aliya Amirova, Lindsay Bearne

Bibliographic record

VenueKeele Research Repository (Keele University) · 2020
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsInstitute of Population and Public Health
Fundersnot available
KeywordsRheumatoid arthritisPhysical medicine and rehabilitationRehabilitationFidelityGaitHealth psychologyMedicinePhysical therapyComputer scienceInternal medicinePublic healthNursing
DOInot available

Abstract

fetched live from OpenAlex

Background
\nMany people with early rheumatoid arthritis (RA) report foot pain and walking disability. Self-reported walking disability two years post-diagnosis is the main predictor of persistent disability. A psychologically informed gait rehabilitation intervention (Great Strides) for early RA was developed to address this, consisting of two compulsory sessions and up to four optional sessions delivered over three months. Physiotherapists and podiatrists received bespoke training to deliver Great Strides, incorporating motivational interviewing (MI) and behaviour change techniques (BCTs), to help patients to complete their walking exercises at home. The aim of this study was to assess fidelity of delivery within the Gait Rehabilitation in Early Arthritis Trial (GREAT) feasibility study.
\n
\nMethods
\nFour physiotherapists and two podiatrists delivered 78 Great Strides sessions across three centres in the UK. All sessions were audio recorded and double coded. The Motivational Interviewing Treatment Integrity (MITI) Rating Scale (scoring ≥4 represents good proficiency) and tailored treatment fidelity measures of the six core elements and 17 BCTs delivered in session 1, five core elements delivered in session 2, and 12 BCTs in session 2-6, were developed to examine fidelity of delivery. Two trained, independent assessors rated audio recordings of Great Strides and assessed the extent to which core elements, aspects of MI and BCTs were delivered across sessions.
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\nResults
\nData from 28 (80%) adult participants across a total of 64 sessions were rated for core components and BCTs and 37 (50%) of sessions were analysed for MI. Relational (score=4.4) and technical (score=4.2) aspects of MI were delivered with good fidelity across the whole sample. The 6 core elements and 7 BCTs in Session 1 were conveyed with high (over 80%) treatment fidelity, but 10 further BCTs were not consistently delivered (range 23-69%). In session 2, the 5 core elements and 3 BCTs were provided with high fidelity, but another 9 BCTs were not reliably delivered (range 11-56%). Sessions 3 and 4 reliably delivered 3 out of 12 BCTs and only one session 5 and 6 was delivered. Inter-rater reliability showed agreement of over 80% was reached between raters for all sessions (range 82-87%).
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\nConclusion
\nPhysiotherapists and podiatrists were able to deliver the core elements of GREAT sessions with high fidelity and fidelity assessment methods were appropriate. Results showed a maximum of 4 sessions was sufficient. However, treatment fidelity might be enhanced with further training or greater on-going support, as findings suggested clinicians (physiotherapists) with previous MI experience were more proficient at offering key elements of MI. Additionally, the Great Strides intervention could be amended to improve delivery, as research shows complex interventions should consider mandatory BCTs alongside optional ones, depending on the needs of individual participants.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.061
GPT teacher head0.323
Teacher spread0.262 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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
Published2020
Admission routes1
Has abstractyes

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