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Record W2138849298 · doi:10.1111/pme.12130

Improving Pain Practices Through Core Competencies

2013· letter· en· W2138849298 on OpenAlexaff
Judy Watt‐Watson, Philip J. Siddall

Bibliographic record

VenuePain Medicine · 2013
Typeletter
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCore competencyMedicineCurriculumHealth professionalsPain managementNursingHealth careMedical educationMEDLINEPsychologyPhysical therapyPedagogy

Abstract

fetched live from OpenAlex

Recent evidence reveals the continuing lack of pain content in health science curricula ⇓ despite the need worldwide to improve pain management practices. Comprehensive pain assessment and management is multidimensional and requires collaboration that reflects competencies in pain knowledge and skill attained by all health professionals. The Institute of Medicine has pointed to the need for health professionals to have greater pain knowledge and skills to participate in the cultural change needed to more successfully help people with pain ⇓. As well, the World Health Organization has suggested that collaborative practice results in more effective health service and delivery and more positive patient outcomes ⇓. However, collaboration will not occur if health professionals do not understand each others' roles and expertise and if they do not have a common language, for example, to discuss patient assessment and management issues. Although evidence for interprofessional education supports positive health outcomes, few health science programs offer the …

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)0.009
metaresearch head score (Gemma)0.069
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.069
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.064
GPT teacher head0.355
Teacher spread0.291 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations11
Published2013
Admission routes1
Has abstractyes

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