Feasibility, Acceptability, and Potential Effects of a Digital Oral Anticancer Agent Intervention: Protocol for a Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Individuals taking oral anticancer agents (OAAs) often face important challenges, requiring more timely informational support, ongoing monitoring, and side effect management. OBJECTIVE: This study, guided by the Self-Efficacy Theory, aims to assess the feasibility, acceptability, and potential effects of a comprehensive, digital OAA intervention. METHODS: A 2-arm, mixed methods, pilot randomized controlled trial took place at a large university-affiliated cancer center in Montreal, Quebec, Canada. Participants (N=52) completed baseline self-report e-questionnaires and subsequently were randomly assigned to the experimental group (intervention plus usual care, n=26) or control group (usual care only, n=26). The study intervention, designed to increase medication adherence via medication adherence self-efficacy and decreased symptom distress, included (1) OAA informational videos, (2) OAA-related e-handouts and other supportive resources, (3) nurse-led follow-up calls, and (4) e-reminders to take OAAs. The e-questionnaires were completed once a week for the first month and every 2 weeks for the subsequent 4 months, or until OAA treatment was completed. A subset from both groups (n=20) participated in semistructured interviews once they completed the study requirements. Study feasibility is assessed using recruitment, retention, and response rates, as well as intervention uptake. Through e-questionnaires and exit interviews, intervention acceptability is to be assessed prospectively at baseline and retrospectively upon study completion. Potential effects are then assessed via medication adherence self-efficacy, medication adherence self-report, and symptom distress. RESULTS: Data collection was completed by December 2023 with a final sample size of 41. Results are expected to be published in 2025. CONCLUSIONS: This study relies on a theoretically based, OAA digital intervention with modalities tailored to the needs and preferences of participants. The use of quantitative and qualitative methods enriches our understanding of the potential contributions of the intervention. In addition, following participants over the course of treatment captures potential changes in oral treatment-related processes and outcomes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04984850; https://www.clinicaltrials.gov/study/nct04984850. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55475.
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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 | 0.057 | 0.042 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.076 | 0.012 |
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".