Development and Initial Validation of a Systemic Lupus Erythematosus–Specific Measure of the Extent of and Reasons for Medication Nonadherence
Bibliographic record
Abstract
OBJECTIVE: Medication nonadherence is common in patients with systemic lupus erythematosus (SLE) and negatively affects outcomes. To better recognize and address nonadherence in this population, there is a need for an easily implementable tool with interpretable scores. Domains of Subjective Extent of Nonadherence (DOSE-Nonadherence) is a measure that captures both extent of and reasons for nonadherence. We refined and evaluated DOSE-Nonadherence for patients with SLE. METHODS: We refined the reasons for the nonadherence domain of DOSE-Nonadherence through rheumatologist feedback and patient cognitive interviewing. We then administered the refined instrument to patients prescribed oral SLE medications and compared the results to the Beliefs About Medicines Questionnaire (BMQ), the Medication Adherence Self-Report Inventory (MASRI), medication possession ratios (MPRs), and hydroxychloroquine (HCQ) blood levels using Pearson correlations. RESULTS: Five rheumatologists provided feedback; 16 patients (median age 43 yrs, 100% female, 50% Black) participated in cognitive interviews and 128 (median age 49 yrs, 95% female, 49% Black, 88% on antimalarials, and 59% on immunosuppressants) completed the refined instrument. Items assessing extent of nonadherence produced reliable scores (α 0.89) and identified 47% as nonadherent. They showed convergent validity with MASRI (r = -0.57), HCQ blood levels (r = -0.55), to a lesser extent MPRs (r = -0.34 to -0.40), and discriminant validity with BMQ domains (r = -0.27 to 0.32). Nonadherent patients reported on average 3.5 adherence barriers, the most common being busyness/forgetting (62%), physical fatigue (38%), and pill fatigue (33%). CONCLUSION: Our results support the reliability and validity of DOSE-Nonadherence for SLE medications. This refined instrument, DOSE-Nonadherence-SLE, can be used to identify, rigorously study, and guide adherence intervention development in SLE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".