A randomized controlled trial to assess the influence of a picture-based antiemetic medication calendar on medication-taking behavior in adults receiving chemotherapy
Bibliographic record
Abstract
Objective A prospective open-label randomized controlled trial to assess the role of a picture-based medication calendar on adherence to antiemetic regimens for adult patients receiving chemotherapy and assess the effect on other medication taking behaviors as well as patient satisfaction with the tool. Methods Participants were randomly assigned 1:1 to routine care with or without calendar. Results Adherence, stratified by education (university or postgraduate, p = 0.09; grade school, high school or college p = 0.32), was non-significantly different between study arms. At least 70% of intervention arm participants moderately or completely agreed that the calendar helped with medication taking behaviors. There was no statistical difference between study arms for perceived regimen complexity ( p = 0.16). Medication Use and Self Efficacy score (adjusted for age) used to assess perceived self-efficacy with medication taking behaviors were not statistically significant between study arms ( p = 0.09). Conclusion The picture-based medication calendar did not statistically affect adherence to scheduled antiemetics among outpatients receiving chemotherapy for solid organ tumor origins. However, participants indicated that the calendar was effective for keeping track of medications, had an easy-to-understand layout, and provided help around when and how to take medications related to the oncology regimen.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".