Androgen deprivation therapy's impact on the mood of prostate cancer patients as perceived by patients and the partners of patients
Bibliographic record
Abstract
OBJECTIVE: To assess the relationship between of androgen deprivation therapy (ADT) and the mood of prostate cancer (PCa) patients and partners of PCa patients. METHODS: PCa patients (n = 295) and partners of patients (n = 84) completed an online survey assessing the patients' current mood and mood prior to treatment, relationship adjustment, and sexual function. We compared men on ADT to men who received non-hormonal treatments for their PCa. RESULTS: Patients currently treated with ADT (n = 82) reported worsened mood as measured by the Profile of Mood States compared to those not on ADT (n = 213). The negative impact of ADT on mood, however, was reduced in older patients. Partners of patients on ADT (n = 42) reported similar declines in the patient's mood that patients reported, but to a greater degree than patient-reported levels. CONCLUSIONS: Our data support ADT's impact on PCa patients' mood and verify that partners concurrently see the effects. The psychological changes related to ADT can impact relationships and affect the quality of life of both PCa patients and partners. Patients and their partners are likely to benefit from being well informed about the psychological effects of androgen deprivation on men beginning ADT. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".