Psychometric Properties of Patient-reported Outcome Measures to Assess Resilience in Individuals with Musculoskeletal Pain or Rheumatic Conditions
Bibliographic record
Abstract
OBJECTIVES: The objective of this systematic review was to provide a comprehensive overview of the measurement properties of patient-reported outcome measures (PROMs) used to assess resilience in individuals with musculoskeletal and rheumatic conditions. METHODS: Four electronic databases (MEDLINE, CINAHL, PsycINFO, and Web of Science) were searched. Studies assessing any measurement property in the target populations were included. Two reviewers independently screened all studies and assessed the risk of bias using the COSMIN checklist. Thereafter, each measurement property of each PROM was classified as sufficient, insufficient, or inconsistent based on the COSMIN criteria for good measurement properties. RESULTS: Four families of PROMs [Brief Resilient Coping Scale (BRCS); Resilience Scale (RS-18); Connor-Davidson Resilience Scale (CD-RISC-10 and CD-RISC-2); and Pain Resilience Scale (PRS-14 and PRS-12)] were identified from the 9 included studies. Even if no PROM showed sufficient evidence for all measurement properties, the PRS and CD-RISC had the most properties evaluated and showed the best measurement properties, although responsiveness still needs to be assessed for both PROMs. Both PROMs showed good levels of reliability (intraclass coefficient correlation 0.61 to 0.8) and good internal consistency (Cronbach's alpha ≥0.70). Minimal detectable change values were 24.5% for PRS and between 4.7% and 29.8% for CD-RISC. DISCUSSION: Although BRCS, RS-18, CD-RISC, and PRS have been used to evaluate resilience in individuals with musculoskeletal and rheumatic conditions, the current evidence only supports the use of PRS and CD-RISC in this population. Further methodological studies are therefore needed and should prioritize the assessment of reliability and responsiveness.
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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 | 0.035 | 0.143 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".