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Record W3014913265 · doi:10.1111/nuf.12453

Implementation of a clinical practice guideline in a primary care setting for the prevention and management of obesity in adults

2020· article· en· W3014913265 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNursing Forum · 2020
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsnot available
Fundersnot available
KeywordsOverweightMedicineGuidelineWeight managementObesityHealth careFamily medicinePopulationManagement of obesityBest practiceWeight lossNursingGerontologyEnvironmental health

Abstract

fetched live from OpenAlex

Over two-thirds of American adults have obesity or overweight, increasing the risk of comorbidities, mortality, and healthcare costs. Despite this growing issue, screening and counseling for an unhealthy weight are not common in primary care and clinical practice guidelines (CPGs) for prevention and management of obesity are underutilized. Following the stepwise approach outlined in the Registered Nurses' Association of Ontario Toolkit: Implementation of Best Practice Guidelines, the Institute for Clinical Systems Improvement: Prevention and Management of Obesity for Adults were implemented in a primary care office in Lexington, KY. Education was implemented with providers and staff. An assessment of readiness for change was completed at check-in and customizable phrases were built into the electronic health record. After a 12-week implementation, providers were consistently assessing for comorbidities, setting goals, and managing weight in those with obesity using evidence-based strategies. Readiness for change was being documented in less than 40% of those patients. For those with overweight providers were assessing readiness for change in only 30% of patients and were setting goals in just over 40% of patients. After the implementation, care more closely followed the CPG but additional steps are necessary to improve the prevention and management of obesity in this population.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.100
GPT teacher head0.560
Teacher spread0.460 · 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