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Record W2588958935 · doi:10.1177/0898010117693539

Treatment-Seeking Behaviors of Persons With Rheumatoid Arthritis

2017· article· en· W2588958935 on OpenAlexaboutno aff
Judith M. Schlaeger, Keesha Powell-Roach, Mary Golas, Miho Takayama, Diana J. Wilkie

Bibliographic record

VenueJournal of Holistic Nursing · 2017
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyRheumatoid arthritisJoint painWeaknessMcGill Pain QuestionnaireOsteoarthritisTelephone interviewAlternative medicineInternal medicineSurgeryVisual analogue scale

Abstract

fetched live from OpenAlex

PURPOSE: Describe perceptions of patients with rheumatoid arthritis (RA) regarding disease-related pain, tendency to tell others about their pain, and treatments used since diagnosis. DESIGN: Cross sectional, exploratory. METHOD: A total of 63 participants responded to telephone interview about their treatments and tendency to tell others about their RA pain. They also responded to McGill Pain Questionnaire and Health Assessment Questionnaire (HAQ) items. Participants marked pain location on mailed body outlines. FINDINGS: RA diagnosis occurred an average of 11 years prior. Mean HAQ Standard Disability Index score was 1.26. Previous week symptoms were joint pain (97%), joint swelling (83%), decreased movement/function (83%), fatigue (70%), muscle weakness (65%). Mean morning stiffness duration was 120 ± 137 minutes. Mean pain intensity was 1.15 ± 0.6 at its least and 3.8 ± 1.1 at its worst. 65% were not satisfied with pain levels. 57% stated a tendency not to tell others about their pain; 43% tended to tell. 78% used medications and alternative therapies, none solely used alternative therapies, and 22% only used medications. CONCLUSIONS: RA patients reported high rates of alternative therapy use. Dissatisfaction with pain levels indicates need for improved pain management. Not talking about pain lends insights into the importance of teaching patients to communicate their pain to others.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.037
GPT teacher head0.342
Teacher spread0.305 · 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 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

Citations16
Published2017
Admission routes1
Has abstractyes

Explore more

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