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Record W2232934952 · doi:10.1155/2000/640173

Support for a Common Metric for Pediatric Pain Intensity Scales

2000· article· en· W2232934952 on OpenAlexaff
Carl L. von Baeyer, Carrie L. Hicks

Bibliographic record

VenuePain Research and Management · 2000
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIntensity (physics)Metric (unit)MedicinePhysicsEngineeringOpticsOperations management

Abstract

fetched live from OpenAlex

Institutional adoption of routine measurement of pediatric pain has been impeded partly by the profusion of different metrics (eg, 0 to 5, 0 to 6, 0 to 10, 0 to 100) for reporting pain intensity on various instruments. The present paper discusses the importance of adopting a common metric, that is, a single numbering system on which estimates of pain intensity from various sources can be recorded. To explore both support and reservations concerning the adoption of a common metric, a survey questionnaire was sent in 1999 to an estimated 600 subscribers to the Pediatric Pain Internet Mailing List. Individuals working in pediatric institutions where children′s pain is routinely measured, or where adoption of such measures is planned, were requested to respond by e‐mail or mail. Responses (n=37) were from nurses (49%), physicians (24%), psychologists (7%) and others/unlisted (20%) on four continents. Adoption of a common metric was endorsed by 81% of respondents. Among the possible numbering systems, the 0 to 10 system was strongly favoured (70%) over other options. Respondents commented that adoption of a common metric would improve communication and consistency in measurement both within and among institutions. Some disadvantages, such as staff resistance to altering existing systems, were also suggested. The majority of respondents thought that it would be desirable to adopt a common metric. Among the possible numbering systems, the 0 to 10 system is by far the most favoured. Adopting a common 0 to 10 standard, and adapting existing tools to that metric, would be positive steps toward identifying and relieving children′s pain.

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)0.020
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.691
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.061
GPT teacher head0.380
Teacher spread0.320 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations44
Published2000
Admission routes1
Has abstractyes

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