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Pain in Women with Relapsing-Remitting Multiple Sclerosis and in Healthy Women

2008· article· en· W2047186240 on OpenAlexaboutno aff
Pamela Newland

Bibliographic record

VenueJournal of Neuroscience Nursing · 2008
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersSigma Theta Tau International
KeywordsMultiple sclerosisRelapsing remittingMedicineMEDLINEPhysical therapyPsychologyPsychiatryPolitical science

Abstract

fetched live from OpenAlex

The purpose of this study was to examine multidimensional aspects of pain in women with relapsing-remitting multiple sclerosis (RRMS) and in healthy women. A cross-sectional, comparative design was used. The convenience sample included 40 women with RRMS and 40 healthy women. Participants completed the Brief Pain Inventory-Long Form and the McGill Pain Questionnaire-Short Form. The women with RRMS had a significantly higher presence of pain (p = .005), present pain intensity (p = .02), average pain intensity (p = .001), pain interference (p = .0008), and pain in different locations (p = .02) than healthy women. Pain has significant nursing implications for women with RRMS. Women with RRMS could benefit from a comprehensive pain assessment and management strategy. Nursing care should be designed to focus on interventions for minimizing and managing pain in women with RRMS.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.322
Teacher spread0.235 · 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 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

Citations9
Published2008
Admission routes1
Has abstractyes

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