Measuring What Matters: A Qualitative Study of the Relevance and Clinical Utility of PROMIS Surveys in Systemic Lupus Erythematosus
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relevance and clinical utility of the Patient-Reported Outcomes Measurement Information System (PROMIS) surveys in patients with systemic lupus erythematosus (SLE). METHODS: Adults with SLE receiving routine outpatient care at a tertiary care academic medical center participated in a qualitative study. Patients completed PROMIS computerized adaptive tests (CATs) in 12 selected domains and rated the relevance of each domain to their experience with SLE. Focus groups and interviews were conducted to elucidate the relevance of the PROMIS surveys, identify additional domains of importance, and explore the utility of the surveys in clinical care. Focus group and interview transcripts were coded, and a thematic analysis was performed using an iterative inductive process. RESULTS: Twenty-eight women and 4 men participated in 4 focus groups and 4 interviews, respectively. Participants endorsed the relevance and comprehensiveness of the selected PROMIS domains in capturing the effect of SLE on their lives. They ranked fatigue, pain interference, sleep disturbance, physical function, and applied cognition abilities as the most salient health-related quality of life (HRQOL) domains. They suggested that the disease-agnostic PROMIS questions holistically captured their lived experience of SLE and its common comorbidities. Participants were enthusiastic about using PROMIS surveys in clinical care and described potential benefits in enabling disease monitoring and management, facilitating communication, and empowering patients. CONCLUSION: PROMIS includes the HRQOL domains that are of most importance to individuals with SLE. Patients suggest that these universal tools can holistically capture the impact of SLE and enhance routine clinical care.
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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 | 0.041 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".