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Record W2289646373 · doi:10.1155/2016/1024985

Dispositional Affect in Unique Subgroups of Patients with Rheumatoid Arthritis

2016· article· en· W2289646373 on OpenAlexaff
Danielle B. Rice, Swati Mehta, Janet Pope, Manfred Harth, Allan Shapiro, Robert Teasell

Bibliographic record

VenuePain Research and Management · 2016
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsWestern UniversitySt Joseph's Health CareParkwood InstituteLawson Health Research Institute
Fundersnot available
KeywordsMoodAffect (linguistics)AlgorithmMedicineInternal medicinePsychologyMachine learningClinical psychologyComputer science

Abstract

fetched live from OpenAlex

Background. Patients with rheumatoid arthritis may experience increased negative outcomes if they exhibit specific patterns of dispositional affect. Objective. To identify subgroups of patients with rheumatoid arthritis based on dispositional affect. The secondary objective was to compare mood, pain catastrophizing, fear of pain, disability, and quality of life between subgroups. Methods. Outpatients from a rheumatology clinic were categorized into subgroups by a cluster analysis based on dispositional affect. Differences in outcomes were compared between clusters through multivariate analysis of covariance. Results. 227 patients were divided into two subgroups. Cluster 1 (n = 85) included patients reporting significantly higher scores on all dispositional variables (experiential avoidance, anxiety sensitivity, worry, fear of pain, and perfectionism; all p < 0.001) compared to patients in Cluster 2 (n = 142). Patients in Cluster 1 also reported significantly greater mood impairment, pain anxiety sensitivity, and pain catastrophizing (all p < 0.001). Clusters did not differ on quality of life or disability. Conclusions. The present study identifies a subgroup of rheumatoid arthritis patients who score significantly higher on dispositional affect and report increased mood impairment, pain anxiety sensitivity, and pain catastrophizing. Considering dispositional affect within subgroups of patients with RA may help health professionals tailor interventions for the specific stressors that these patients experience.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.029
GPT teacher head0.339
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 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

Citations6
Published2016
Admission routes1
Has abstractyes

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