Determinants of health-related quality of life in adults living with rheumatoid arthritis: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To systematically review contemporary studies identifying health-related quality of life (HRQoL) determinants in rheumatoid arthritis (RA) and synthesize the evidence. METHODS: Three electronic databases were searched for cross-sectional or prospective cohort studies published 2000 or later that identified HRQoL determinants using multivariable prediction models and evaluated HRQoL using the SF-36/12/8/6D or EQ-5D. Two authors conducted screening, data extraction, and quality assessment. Findings were synthesized using a narrative synthesis approach. RESULTS: Twenty-one studies were included. Seventy determinants were evaluated. Determinants were classified into five domains: (i) sociodemographic, (ii) RA-related, (iii) comorbidities and general health, (iv) health behaviours, and (v) psychosocial. RA-related determinants were the most studied determinants. Forty-four determinants were identified as statistically significant HRQoL determinants. Age and gender were the most evaluated determinants in the sociodemographic domain, but associations between older age and female gender and better HRQoL were inconsistent. Disease duration, disease activity, and physical function were the most evaluated determinants in the RA-related domain. Higher disease activity and worse physical function were associated with lower HRQoL, but association between longer disease duration and HRQoL was inconsistent. All comorbidities identified were associated with lower HRQoL. Exercise and sleep were the only significant determinants in the health behaviours domain and were associated with better HRQoL. Anxiety and depression were the most evaluated psychosocial variables and were associated with lower HRQoL. CONCLUSION: HRQoL determinants were identified from multiple domains. The existing literature consists mostly of cross-sectional studies. More prospective studies are needed to assess temporal relationship between determinants and HRQoL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".