Impact of a Brief Educational Intervention on Glaucoma Persistence: A Randomized Controlled Clinical Trial
Bibliographic record
Abstract
PURPOSE: To determine whether two sessions of a glaucoma educational intervention resulted in better persistence to glaucoma eye drop therapy compared to normal care. METHODS: A total of 165 patients newly diagnosed with glaucoma who required eye drop therapy were recruited into a randomized clinical trial from the glaucoma clinic at Maisonneuve-Rosemont Hospital in Montreal, Canada. Patients were randomized to either an immediate intervention or normal care. The intervention consisted of two 60-90 minute sessions of education on glaucoma and its management, given in a small group format by a non-practicing ophthalmologist. Persistence to glaucoma medication was examined for 1 year by the use of Hospital medical records and by pharmacy claims records from the Régie de l'assurance maladie du Québec (Quebec Health Insurance Program). A questionnaire was administered, and medication possession ratio calculated. The primary outcome was persistence, defined as having medication available at least 75% of the time. Secondary outcomes included eye drop instillation technique and perception of the importance of eye drop therapy. RESULTS: The intervention group achieved better persistence to eye drop therapy, as 77% of controls and 89% of people receiving the intervention were persistent (p = 0.049). The intervention also resulted in better eye drop instillation technique (p < 0.001) and greater perception of the importance of eye drop therapy (p < 0.001). CONCLUSIONS: Brief instructional sessions offered to newly diagnosed glaucoma patients can result in better persistence rates over 1-year follow-up. Strategies to permanently offer these types of initiatives should be considered.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".