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Record W2128652691 · doi:10.3906/sag-1112-43

Better marital adjustment is associated with lower disease activity in early inflammatory arthritis

2012· article· en· W2128652691 on OpenAlexaff
Sally Mustafa, Karl Looper, Margaret Purden, Phyllis Zelkowitz, Murray Baron

Bibliographic record

VenueTURKISH JOURNAL OF MEDICAL SCIENCES · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineSpouseDiseasePsychological interventionArthritisInternal medicineMarital statusMultivariate analysisC-reactive proteinPhysical therapyInflammatory arthritisPsychiatryInflammation

Abstract

fetched live from OpenAlex

The aim of this study was to examine the association between marital adjustment and disease outcomes in patients with early inflammatory arthritis. Materials and methods: Patients with average disease duration of 7.66 ± 3.79 months were recruited from a larger early inflammatory arthritis registry, which recorded sociodemographic data and disease characteristics. The acute phase reactant C-reactive protein (CRP) levels were measured and disease activity was estimated using the Disease Activity Score in 28 joints (DAS28). Patient and spouse perceived marital adjustment was assessed by the Dyadic Adjustment Scale (DAS). Results: The study sample consisted of 73 patients living with their spouses. The mean age of the study participants was 54.30 ± 12.09 years and 64.4% were female. Patient-perceived marital adjustment (DAS-Patient) was negatively correlated to CRP (P = 0.007) and DAS28 (P = 0.002). On multivariate analysis, DAS-Patient contributed to the dependent variable DAS28 after controlling for CRP. Conclusion: The current study indicates that better marital adjustment is associated with lower disease activity. The possible reciprocal relationship between marital adjustment and illness highlights the relevance for clinicians to include both patients and their spouses in interventions.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.293
Teacher spread0.269 · 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.

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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueTURKISH JOURNAL OF MEDICAL SCIENCESSame topicFamily Support in IllnessFrench-language works237,207