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A brief analysis of Clinical Best Practice Guidelines: Assessment and Management of Pain (Third Edition) by Registered Nurses' Association of Ontario in 2013

2018· article· en· W3029190487 on OpenAlexaboutno aff
Wai Haung Yu, Lihui Liu, Hong Guo, Zhiqi Chen, Qi Liu, Dongqin Kang, Wang Zipan, Jing Wang, Shujin Yue

Bibliographic record

VenueZhonghua xiandai huli zazhi · 2018
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsnot available
Fundersnot available
KeywordsGuidelinePain managementPain assessmentMedicineHealth careClinical PracticeBest practiceNursingPhysical therapyManagement

Abstract

fetched live from OpenAlex

Mismanagement of pain is a burden on individuals, the health care system and the society. Pain is related to a person's life, which seriously affects the patient's physical health and quality of life. This article interprets the main content of Clinical Best Practice Guidelines: Assessment and Management of Pain (Third Edition) published by Registered Nurses' Association of Ontario (RNAO) in 2013, to help clinical nurses get the latest literature of pain assessment and management, so as to improve the level of care and reduce pain in patients. The updated guidelines emphasize that anyone's pain should be recognized and respected, and that individualized pain assessment and management should include relevant biopsycho-social components. In addition, this guideline advocates continuous learning by health care professionals to update knowledge and information on pain assessment and management, and encourages communication among professional teams in order to optimize pain assessment and management. Key words: Practice guideline; Assessment and management of pain; Interpretation

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)0.012
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.198
GPT teacher head0.531
Teacher spread0.333 · 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.

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
Published2018
Admission routes1
Has abstractyes

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