Effects of virtual reality erotica on ejaculate quality of sperm donors: a balanced and randomized controlled cross-over within-subjects trial
Bibliographic record
Abstract
BACKGROUND: Previous research has shown that the type and duration of erotic material that men have access to during masturbation can influence semen parameters. To our knowledge, the use of virtual reality (VR) headsets to present erotica has not previously been studied. We reasoned that, because VR can provide a more immersive experience to the user, semen parameters of masturbatory ejaculates may be altered. METHODS: This study had a balanced and randomized controlled cross-over within-subjects design. 504 ejaculates were collected from 63 sperm donors at 4 locations in Denmark. During masturbation each donor was instructed to observe erotic material either on a touch screen monitor or using a VR headset. The order of each pair of within-subject treatments was randomized by the throw of a dice. Anonymized data were analysed with linear mixed and piecewise structural equation models. RESULTS: Both abstinence period and VR-use influenced the total number of motile spermatozoa ejaculated. For short abstinence periods, VR-use increased the number of motile sperm in the ejaculate. However, the difference between VR and non-VR ejaculates decreased as abstinence period increased such that there was no difference at the mean abstinence period of 58 h. For longer abstinence periods, total motile sperm counts were lower, on average, when men used VR compared to those that did not. CONCLUSION: The use of VR headsets to view erotica had a strong positive effect on the number of motile sperm in an ejaculate when the donor's abstinence time was short (< 24 h). VR-use could improve the ejaculate quality of men who are asked to provide samples after a short period of abstinence, such as men in infertile partnerships producing samples for ART or cancer patients depositing sperm before treatment. TRIAL REGISTRATION: Trial retrospectively registered on 13 July 2022 at ClinicalTrials.gov. Identifier: NCT05457764.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".