A Tailored Electronic Survivorship Care Plan for Prostate Cancer Survivors: A Multicenter Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: Although the provision of a survivorship care plan (SCP) has been recommended after prostate cancer (PCa) treatment, there have been no randomized controlled trials to examine their impact. The objective of this study was to evaluate the effect of a tailored PCa-SCP intervention provided to early-stage PCa survivors. MATERIALS AND METHODS: A prospective, parallel 1:1 randomized controlled trial was conducted at 3 sites across Canada. Early-stage PCa survivors were randomized (n = 189; 64% response rate) to receive PCa-SCP intervention or usual care. Assessments were performed at baseline, 6 months, and 12 months. The primary outcome was change in patient activation (Patient Activation Measure-13); secondary outcomes included satisfaction with information, self-management support, prostate-specific quality of life, cancer worry, health care utilization, and health behaviors. RESULTS: = .05). No other group-by-time differences were detected. CONCLUSIONS: The PCa-SCP intervention did not have a significant effect on patient activation but did increase satisfaction with information and some aspects of self-management support. Although the benefits of the provision of an SCP alone remain unclear, the PCa-SCP intervention is likely a valuable tool that can be built upon as part of a comprehensive approach to enhance the quality of care for PCa survivors. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03017456.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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) | 0.011 | 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".