Evaluating an educational intervention to alleviate distress among men with newly-diagnosed prostate cancer and their partners.
Bibliographic record
Abstract
194 Background: Diagnoses of cancer distress both patients and their partners. Providing accurate information about diagnosis and treatment options promotes active and informed decision-making and can decrease distress and anxiety. We sought to determine whether an education session alleviated distress for both prostate cancer (PC) patients and their partners, and whether their partner’s attendance at the session, as well as specific disease, treatment, and socio-demographic characteristics affect changes in distress levels. Methods: The session consists of a 90-minute didactic presentation, followed by an 8- to 10-minute private session with a urologist and radiation oncologist. We assessed distress using the Distress Thermometer (DT) and compared pre- and post-session distress, and change in distress between patients and partners using matched and unmatched t-tests. We also assessed before-the-session anxiety using the Generalized Anxiety Disorder measure (GAD), and decisional certainty using the Decisional Conflict Scale. Results: 71 patients and 48 partners participated in the study. Attending the session led to a significant reduction in median DT score for both patients (4.0 to 3.0, p = 0.0009) and partners (5.0 vs. 4.0, p = 0.0176). Partners reported higher distress both before and after the session compared to patients (4.9 vs. 3.8, p = 0.025 pre-session and 4.2 vs. 3.1, p = 0.032 post-session). The presence of a partner at the session did not appear to affect patients’ pre- or post-session distress nor the success of the session at alleviating distress. Sociodemographic and clinical characteristics had little effect on distress levels. Conclusions: Our study demonstrates that an interdisciplinary education session is equally effective at alleviating distress for both PC patients and their partners. These results can be used to guide the development of supportive care programs more broadly in terms of their ability to address the physiological and psychological needs of PC patients and their families.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".