Hard Times: Prostate Cancer Patients’ Experiences with Erectile Aids
Bibliographic record
Abstract
BACKGROUND: Prostate cancer (PCa) treatments commonly lead to erectile difficulties. While the mainstay treatment is erectile aids (EAs) to promote erectile recovery, some men never use these treatments and those whose do use EAs often abandon them in the long-term. AIM: The goal of this study was to examine PCa patients' experiences with EAs, to elucidate relationships between experiences with EAs on psychological and sexual well-being, and to explore benefits and drawbacks to EA use. METHODS: A self-report survey including validated questionnaires was administered to examine PCa patients' use and perceptions of helpfulness of EAs, and to characterize associations between use, perceived helpfulness, and psychological and sexual well-being. The survey was followed by an open-ended prompt to explore participants' experiences with EAs. OUTCOMES: We surveyed 260 North American men, up to 25 years after receiving treatment for PCa. Three groups of patients were observed, including those who used EAs and perceived them to be helpful, those who used EAs and perceived them to be unhelpful, as well as a smaller group of patients who never used EAs. RESULTS: Around 80% of the sample were using or had used EAs. Despite the high frequency of use, not all men found EAs helpful. Men who used EAs and found them unhelpful reported poorer psychological and sexual well-being compared to men who didn't use aids or who used EAs but found them helpful. Results indicated both benefits and drawbacks to the use of EAs. Benefits related largely to the efficacy of the aid in promoting erections. A wide range of drawbacks were also reported. CLINICAL IMPLICATIONS: Given the negative sexual and psychological impacts associated with using EAs and finding them unhelpful, we suggest that researchers and health care providers should take care to proactively address potential challenges that are common with EA use, and also to consider the risks of failed attempts with EAs. STRENGTHS & LIMITATIONS: By using both scaled and open-ended questions, a more nuanced picture of the relative benefits and limitations of EA use within the PCa population is presented. As responses were not mandatory, a subset of participants provided comments about the use of EAs. Additionally, the sample was quite homogenous, with mostly white, American and well-educated participants, so it therefore lacks generalizability to other populations. CONCLUSION: This paper illustrates several challenges to EA use, while providing insight into reasons for abandonment of use of EAs. Walker LM, Sears CS, Santos-Iglesias P, et al. Hard Times: Prostate Cancer Patients' Experiences with Erectile Aids. J Sex Med 2021;18:1775-1787.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".