A comparison of patient adherence and preference of packaging method for oral anticancer agents using conventional pill bottles versus daily pill boxes
Bibliographic record
Abstract
Adherence to medications is an important issue in oncology due to the increasing number of anticancer agents, such as targeted therapies, formulated for oral dosing. A prospective, crossover design was utilized in which patients on capecitabine were randomly assigned to one of two packaging methods for one cycle, and then switched over to the alternate packaging method in the subsequent cycle. Twenty-five patients were accrued to this study. Adherence rates were similar when using the daily pill boxes (17/21 = 81%) and when using the conventional pill bottles (18/21 = 86%). However, more patients were satisfied with the daily pill boxes (61% versus 11%, P = 0.027), preferred the daily pill boxes (61% versus 17%, P = 0.061), and thought the daily pill boxes were more helpful in reminding them to take their medications (50% versus 11%, P = 0.070). In conclusion, this small pilot study did not demonstrate that the use of daily pill boxes improved patient adherence with capecitabine, but patient satisfaction and preference for this packaging method were greater than for the conventional pill bottles. Further exploration of this intervention in a larger study is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".