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Record W7073990473

Mobile health biometrics to enhance exercise and physical activity adherence in type 2 diabetes (MOTIVATE-T2D) : Protocol for a feasibility randomised controlled trial

2021· article· en· W7073990473 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialmHealthType 2 diabetesIntervention (counseling)Clinical trialResearch ethicsProtocol (science)TelemedicineAlternative medicineHealth care
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Exercise and physical activity (PA) are fundamental to the treatment of type 2 diabetes. Current exercise and PA strategies for newly diagnosed individuals with type 2 diabetes are either clinically effective but unsuitable in routine practice (supervised exercise) or suitable in routine practice but clinically ineffective (PA advice). Mobile health (mHealth) technologies, offering biometric data to patients and healthcare professionals, may bridge the gap between supervised exercise and PA advice, enabling patients to engage in regular long-term physically active lifestyles. This feasibility randomised controlled trial (RCT) will evaluate the use of mHealth technology when incorporated into a structured home-based exercise and PA intervention, in those recently diagnosed with type 2 diabetes. METHODS AND ANALYSIS: This feasibility multicentre, parallel group RCT will recruit 120 individuals with type 2 diabetes (diagnosis within 5-24 months, aged 40-75 years) in the UK (n=60) and Canada (n=60). Participants will undertake a 6-month structured exercise and PA intervention and be supported by an exercise specialist (active control). The intervention group will receive additional support from a smartwatch and phone app, providing real-time feedback and enabling improved communication between the exercise specialist and participant. Primary outcomes are recruitment rate, adherence to exercise and loss to follow-up. Secondary outcomes include a qualitative process evaluation and piloting of potential clinical outcome measures for a future RCT. ETHICS AND DISSEMINATION: The trial was approved in the UK by the South East Scotland Research Ethics Committee 01 (20/SS/0101) and in Canada by the Clinical Research Ethics Board of the University of British Columbia (H20-01936), and is being conducted in accordance with the Declaration of Helsinki and Good Clinical Practice. Results will be published in peer-reviewed journals and presented at national and international scientific meetings. TRIAL REGISTRATION NUMBERS: ISRCTN14335124; ClinicalTrials.gov: NCT04653532.

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)0.042
metaresearch head score (Gemma)0.034
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 score0.128
Threshold uncertainty score0.430

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.034
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0110.006
Bibliometrics0.0030.004
Science and technology studies0.0040.004
Scholarly communication0.0050.004
Open science0.0040.003
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.1280.023

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 head0.056
GPT teacher head0.328
Teacher spread0.273 · 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
Published2021
Admission routes1
Has abstractyes

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