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Record W1981877992 · doi:10.4236/ojemd.2012.24008

Difficulties in Recruitment for a Randomised Controlled Trial of Lifestyle Intervention for Type 2 Diabetes: Implications for Diabetes Management

2012· article· en· W1981877992 on OpenAlexaff
George A Jelinek, Emily J. Hadgkiss, Craig Hassed, Bernard Crimmins, Peter Schattner, Danny Liew, Rick Kausman, Warrick J. Inder, Siegfried Gutbrod, Tracey Weiland

Bibliographic record

VenueOpen Journal of Endocrine and Metabolic Diseases · 2012
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsManning Diversified Forest Products (Canada)
Fundersnot available
KeywordsMedicineIntervention (counseling)AttritionType 2 diabetesRandomized controlled trialDiabetes mellitusPhysical therapyFamily medicineNursingSurgery

Abstract

fetched live from OpenAlex

Objective: To report our experience of attempting a randomised controlled trial of an intensive lifestyle intervention for early type 2 diabetes delivered in a residential setting. Methods: We established a trial requiring 84 participants (46 standard care and 38 intervention) to detect a 1% difference in HbA1c between intervention and control groups at 12 months, allowing for attrition. Ethics approval was obtained from Monash University. Results: The study was abandoned after five months of consistent promotion due to recruitment failure (four subjects recruited). Conclusion: It appears to be difficult for patients with diabetes to commit to a live-in period of education regarding lifestyle modification as a means of treating the illness. We recommend better education of patients and their doctors about the potential health benefits of lifestyle change to manage type 2 diabetes, and further research into novel methods of delivering lifestyle advice which are both effective and sustainable.

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)0.486
metaresearch head score (Gemma)0.505
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: Methods
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.633

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4860.505
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0040.004
Open science0.0030.003
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0060.002

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 head0.067
GPT teacher head0.387
Teacher spread0.321 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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

Citations2
Published2012
Admission routes1
Has abstractyes

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