Scope of Outcomes in Trials and Observational Studies of Interventions Targeting Medication Adherence in Rheumatic Conditions: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Nonadherence to medications is common in rheumatic conditions and associated with increased morbidity. Heterogeneous outcome reporting by researchers compromises the synthesis of evidence of interventions targeting adherence. We aimed to assess the scope of outcomes in interventional studies of medication adherence. METHODS: We searched electronic databases to February 2019 for published randomized controlled trials and observational studies of interventions with the primary outcome of medication adherence including adults with any rheumatic condition, written in English. We extracted and analyzed all outcome domains and adherence measures with prespecified extraction and analysis protocols. RESULTS: Overall, 53 studies reported 71 outcome domains classified into adherence (1 domain), health outcomes (38 domains), and adherence-related factors (e.g., medication knowledge; 32 domains). We subdivided adherence into 3 phases: initiation (n = 13 studies, 25%), implementation (n = 32, 60%), persistence (n = 27, 51%), and phase unclear (n = 20, 38%). Thirty-seven different instruments reported adherence in 115 unique ways (this includes different adherence definitions and calculations, metric, and method of aggregation). Forty-one studies (77%) reported health outcomes. The most frequently reported were medication adverse events (n = 24, 45%), disease activity (n = 11, 21%), bone turnover markers/physical function/quality of life (each n = 10, 19%). Thirty-three studies (62%) reported adherence-related factors. The most frequently reported were medication beliefs (n = 8, 15%), illness perception/medication satisfaction/satisfaction with medication information (each n = 5, 9%), condition knowledge/medication knowledge/trust in doctor (each n = 3, 6%). CONCLUSION: The outcome domains and adherence measures in interventional studies targeting adherence are heterogeneous. Consensus on relevant outcomes will improve the comparison of different strategies to support medication adherence in rheumatology.
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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 | 0.097 | 0.320 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.020 | 0.017 |
| Bibliometrics | 0.022 | 0.017 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| 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".