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Record W2018228302 · doi:10.1177/1054773804265692

An Exploration of Seniors' Ability to Report Pain

2004· article· en· W2018228302 on OpenAlexaff
Sharon Kaasalainen, Joan Crook

Bibliographic record

VenueClinical Nursing Research · 2004
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRating scaleCognitive impairmentCognitionPain assessmentPhysical therapyMedicinePsychologyClinical psychologyPain managementPsychiatryDevelopmental psychology

Abstract

fetched live from OpenAlex

The purpose of this study was to evaluate the ability of a group of elderly residents to use self-report methods to measure their pain in an accurate fashion. Using a comparative descriptive design, completion rates of three pain assessment tools and the self-report skills of a sample of 130 long-term care residents with varying levels of cognitive impairment were evaluated. The majority of residents with mild to moderate cognitive impairment were able to complete at least one of the verbal pain assessment tools, with the Present Pain Intensity and Numerical Rating Scales being the preferred choices for use in clinical settings. However, the Faces Pain Scale appeared to be more challenging for residents to complete, suggesting that it requires further testing before it can be recommended for clinical use.

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)0.003
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.250
GPT teacher head0.559
Teacher spread0.310 · 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.

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

Citations45
Published2004
Admission routes1
Has abstractyes

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