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Record W2158094563 · doi:10.9778/cmajo.20130040

Guideline harmonization and implementation plan for the BETTER trial: Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Family Practice

2014· article· en· W2158094563 on OpenAlexafffundvenue
Denise Campbell‐Scherer, Julia H. Rogers, Donna Manca, Kelly Lang‐Robertson, Samira Bell, Ginetta Salvalaggio, Michelle Greiver, Christina Korownyk, Doug Klein, June Carroll, Meldon Kahan, James Meuser, Sandy Buchman, R M S Barrett, Eva Grunfeld

Bibliographic record

VenueCMAJ Open · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsOntario Institute for Cancer ResearchTD Bank GroupCollege of Family Physicians of CanadaUniversity of TorontoMount Sinai HospitalNorth York General HospitalSt Joseph's Health CentreInstitute for Work & HealthCentre for Social InnovationUniversity of Alberta
FundersDepartment of Family and Community Medicine, University of TorontoUniversity of TorontoUniversity of Alberta
KeywordsGuidelineMedicineDieticiansRandomized controlled trialHarmonizationFamily medicineClinical trialMEDLINENursingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The aim of the Building on Existing Tools to Improve Chronic Disease Prevention and Screening in Family Practice (BETTER) randomized controlled trial is to improve the primary prevention of and screening for multiple conditions (diabetes, cardiovascular disease, cancer) and some of the associated lifestyle factors (tobacco use, alcohol overuse, poor nutrition, physical inactivity). In this article, we describe how we harmonized the evidence-based clinical practice guideline recommendations and patient tools to determine the content for the BETTER trial. METHODS: We identified clinical practice guidelines and tools through a structured literature search; we included both indexed and grey literature. From these guidelines, recommendations were extracted and integrated into knowledge products and outcome measures for use in the BETTER trial. End-users (family physicians, nurse practitioners, nurses and dieticians) were engaged in reviewing the recommendations and tools, as well as tailoring the content to the needs of the BETTER trial and family practice. RESULTS: In total, 3-5 high-quality guidelines were identified for each condition; from these, we identified high-grade recommendations for the prevention of and screening for chronic disease. The guideline recommendations were limited by conflicting recommendations, vague wording and different taxonomies for strength of recommendation. There was a lack of quality evidence for manoeuvres to improve the uptake of guidelines among patients with depression. We developed the BETTER clinical algorithms for the implementation plan. Although it was difficult to identify high-quality tools, 180 tools of interest were identified. INTERPRETATION: The intervention for the BETTER trial was built by integrating existing guidelines and tools, and working with end-users throughout the process to increase the intervention's utility for practice. TRIAL REGISTRATION: ISRCTN07170460.

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)0.498
metaresearch head score (Gemma)0.638
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.498
Threshold uncertainty score0.619

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4980.638
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0070.014
Bibliometrics0.0170.020
Science and technology studies0.0040.005
Scholarly communication0.0180.014
Open science0.0090.015
Research integrity0.0120.015
Insufficient payload (model declined to judge)0.0060.004

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 head0.603
GPT teacher head0.677
Teacher spread0.074 · 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.

Study designNot applicable
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

Citations31
Published2014
Admission routes3
Has abstractyes

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