What methods are used to study the association between medication adherence trajectories, estimated with the group-based trajectory modeling (GBTM) method, and health-related outcomes?—a protocol for a systematic review
Bibliographic record
Abstract
BACKGROUND: The group-based trajectory modeling (GBTM) method is increasingly used in pharmacoepidemiologic studies to describe medication adherence trajectories over time. However, assessing the associations between these medication adherence trajectories and health-related outcomes remains challenging. The purpose of this review is to identify and systematically review the methods used to assess the association between medication adherence trajectories, estimated from the GBTM method, and health-related outcomes. METHODS: We will conduct a systematic review according to the recommendations of the Cochrane handbook for systematic reviews of interventions 6.2. Results will be reported following PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-analyses) recommendations. We will search in the following databases: PubMed, Embase, PsycINFO, Web of Science, CINAHL, and Cochrane Library. Two reviewers will independently select articles and extract data. Discrepancies at every step will be resolved through discussion, and consensus will be reached for all disagreed articles. A third reviewer will act as a referee if needed. We will produce tables to synthesize the modalities used to estimate medication adherence trajectories with GBTM. We will also synthesize the modalities used to assess the association between these medication adherence trajectories and health-related outcomes by identifying the types of health-related outcomes studied and how they are defined, the statistical models used, and how the medication adherence trajectories were used in these models, and the effect measure yield. We will also review the limitations and biases reported by the authors and their attempts to mitigate them. We will provide a narrative synthesis. DISCUSSION: This review will provide a thorough exploration of the strategies and methods used in medication adherence research to estimate the associations between medication adherence trajectories, estimated with GBTM, and the different health-related outcomes. It will represent the first crucial steps toward optimizing these methods in adherence studies. SYSTEMATIC REVIEW REGISTRATION: Prospero CRD42021213503 .
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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 | 0.259 | 0.357 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.022 | 0.018 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.026 | 0.007 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".