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Record W4372060068 · doi:10.1093/sexmed/qfad016

“Blue balls” and sexual coercion: a survey study of genitopelvic pain after sexual arousal without orgasm and its implications for sexual advances

2023· article· en· W4372060068 on OpenAlexafffund
Samantha L Levang, Megan S. Henkelman, Robin Neish, Wendy Zukerman, Blythe Terrell, Victoria Jackman, Shannon Coyle, Jamin Brahmbhatt, Caroline F. Pukall

Bibliographic record

VenueSexual Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsMemorial University of NewfoundlandQueen's University
FundersCanadian Institutes of Health Research
KeywordsOrgasmVaginaVulvaSexual arousalClitorisSex organPsychologyThematic analysisPenisGynecologyMedicineClinical psychologySexual dysfunctionSexual behaviorPsychiatryQualitative researchSurgeryBiology

Abstract

fetched live from OpenAlex

Background: Blue balls/vulva has received increasing interest from the public in recent years, sparking debate about genital physiology, controversy around "sexual release" as a treatment for this type of pain, and sexual consent. Aim: This cross-sectional, mixed-methods online study aimed to evaluate the general understanding and frequency of blue balls/vulva and whether individuals have ever been pressured to continue sexual activity because of a partner's fears of experiencing pain without orgasm. Methods: A total of 2621 individuals with a penis (n = 1483) or vagina (n = 1138) were recruited for an online survey on the experience of "blue balls/vulva." Quantitative analyses consisted primarily of descriptive statistics and chi-square analyses. Between-group differences were analyzed (based on whether respondents reported having a penis or vagina), and responses to open-ended questions were examined via thematic analysis. Outcomes: The primary outcomes of interest were reports of the belief in blue balls/vulva, the frequency and pain characteristics of blue balls/vulva, and the incidence of being pressured to continue sexual activity due to a partner's fears of experiencing pain without orgasm. Results: Results indicated that significantly more individuals with a penis than a vagina reported believing that blue balls are real, endorsed experiencing pain when they approached orgasm but did not ejaculate, and reported moderate and severe pain. Significantly more individuals with a vagina than a penis reported being pressured into a sexual act due to a partner's fear of experiencing pain without orgasm. Results from the thematic analysis indicated that participants recognized that those with a vagina are expected to act sexually to prevent their partners' experience of blue balls, despite agreement that this phenomenon should not be used to coerce or manipulate partners into engaging sexually. Clinical Implications: Education on the frequency of this phenomenon and methods to relieve pain alternative to partnered sexual activity should be addressed in patients who present with this condition. Strengths and Limitations: Although the survey was brief, it provided information from a relatively large sample about whether people believe that this phenomenon exists, how many experience it, how painful it is, and how often it has been used as an excuse for a partner to continue sexual activity. Conclusion: Results indicated that severe pain exists in a minority of individuals, that solitary sexual and nonsexual activities can help to alleviate the discomfort, and that this pain is not a valid reason to continue unwanted sexual activity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.081
GPT teacher head0.364
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2023
Admission routes2
Has abstractyes

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