Androgen deprivation therapy educational program: A Canadian true nth initiative.
Bibliographic record
Abstract
243 Background: Androgen deprivation therapy (ADT) is commonly prescribed for advanced prostate cancer (PCa) patients, but ADT has many side effects that can impair patients’ quality of life. In various Canadian cities, we are running an educational program to help PCa patients and their partners deal with the side effects of ADT, and maintain a strong relationship with each other while on ADT. Methods: Patients, who are about to start or have been on ADT, and their partners are invited to attend an educational program. Each patient is given a copy of the book Androgen Deprivation Therapy: An essential guide for men with prostate cancer and their partners (Wassersug et al., 2014) and attends a 1.5 hour educational class, where they learn strategies for managing ADT side effects and how to effectively make healthier lifestyle changes using goal-setting exercises. At the end of the class, participants are given the option to attend a monthly follow-up session. To evaluate the effectiveness of the program, participants are asked to complete questionnaire package before attending the class and again 2-3 months later. Results: As of August 2015, 179 patients and 113 partners have attended the ADT Educational Program at Victoria, Vancouver, and Calgary. About 40% of patients returned for the follow-up session. 62 attendees participated in the research evaluation portion of the program. Uniquely designed for this study, the questionnaire package assesses ADT side effect frequency, bother associated with side effects, use of management strategies, and self-efficacy regarding side effect management. An assessment of physical activity and relationship adjustment, and feedback about the class are also included. Conclusions: Patients and partners appreciate being informed about ADT side effects managements and how to make healthier lifestyle changes while on ADT. It remains to be seen how effective the program is in limiting the bother from ADT side effects and helping couples maintain a strong dyadic relationship in the fact of the challenges brought on by ADT. Good enrollment in the in-person program in the 3 cities has propelled the development of the program in Halifax and Toronto starting in fall 2015, and an online version to be available in early 2016.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".