A Non-Randomized Comparison of Online and In-Person Formats of the Canadian Androgen Deprivation Therapy Educational Program: Impacts on Side Effects, Bother, and Self-Efficacy
Bibliographic record
Abstract
Although Androgen Deprivation Therapy (ADT) is effective in controlling prostate cancer (PCa) and increasing survival, it is associated with a myriad of side effects that cause significant morbidity. Previous research has shown that PCa patients starting on ADT are neither fully informed nor well-equipped to manage the breadth of ADT’s side effects. The ADT Educational Program (a 1.5 h interactive class plus a book) was developed as an evidence-based resource for patients dealing with ADT. Our aim here was to compare the efficacy of an online version of the class with a previously assessed in-person version of the class. Using mixed MANOVAs within a non-randomized comparison design, we assessed: (1) changes in patients’ experiences of self-efficacy to manage and bother associated with side effects approximately 10 weeks after attending a class, and (2) potential differences in these variables between online and in-person class formats. Side effect bother decreased from pre- to post-class but did not differ between in-person (n = 94) and online (n = 137) class cohorts. While self-efficacy to manage side effects was slightly higher post-class in both cohorts, the increase was not statistically significant. Average self-efficacy ratings were significantly higher among in-person versus online class participants (p < 0.05; ηp2 = 0.128). Both online and in-person classes are associated with a significant reduction in the severity of side effect bother reported by PCa patients, suggesting non-inferiority of online versus in-person formats. Online classes offer greater accessibility to the program for patients outside the reach of in-person classes, increasing the availability of the program to more PCa patients and family members across Canada.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".