(031) PAIN MITIGATION STRATEGIES AMONG FEMALES EXPERIENCING PAINFUL INTERCOURSE WHILE ATTEMPTING PREGNANCY
Bibliographic record
Abstract
Abstract Introduction Pain during intercourse is a relatively common experience among reproductive-aged females but is often not discussed with healthcare providers. In the context of attempting pregnancy, people may find themselves unable to abstain from painful intercourse and so may attempt to mitigate their pain. Despite this connection, research evaluating experiences of painful intercourse among pregnancy planners is sparse. Objective To characterize pain mitigation strategies among females attempting pregnancy experiencing painful intercourse. Methods We used data from Pregnancy Study Online (PRESTO), an online preconception cohort study of females residing in the United States or Canada and actively attempting a pregnancy with a male partner without the use of assisted reproductive technology (2020-2023). To be eligible for this study, participants must have completed the optional Sexual Health and Well-Being Study within one year of cohort enrollment and before reporting a pregnancy (N=1,545). Participants were asked whether they experienced any pain during vaginal penetration in the past 4 weeks. Response options were five frequency options ranging from ‘Never or rarely’ to ‘Almost always or always.’ Those who responded that they experienced pain more frequently than ‘Never or rarely’ were categorized as experiencing any painful penetration and asked to rate the usual intensity of the pain on a scale of 1 to 10 and if they tried any strategies to mitigate the pain. For each reported strategy, participants were asked to rank its perceived efficacy at mitigating their pain on a scale of 1 ‘Never effective’ to 5 ‘Always Effective.’ Response options of ‘Often effective’ or ‘Always effective’ were grouped for descriptive analysis. Strategy effectiveness was also evaluated stratified by high pain (usual intensity ≥5) versus not high pain. Results Four-hundred and eighty participants (31%) reported experiencing any painful penetration in the past 4 weeks. The mean pain intensity was 3.6 (standard deviation [sd]=1.7). The most common reported strategies to try to mitigate pain were changing sexual positions (66%), using lubricant (59%), trying to finish intercourse quickly (49%), having an orgasm before penetration (32%) and only allowing partial vaginal penetration by the penis (30%). The most effective strategy was lubricant use, with 72% of participants reporting that strategy to be often or always effective, followed by partial penetration (66%), changing position (64%), and orgasm (62%). The least effective strategy was trying to finish quickly, with only 30% of participants saying that was often or always effective. The effectiveness of a given strategy changed with pain intensity, with all strategies being less likely to be often or always effective among those with higher pain intensity. Conclusions Among a sample of pregnancy planners, strategies to mitigate painful penetration varied. In general, most strategies were perceived as being often or always effective at mitigating pain, though less so for people with more intense pain. Because abstaining from painful intercourse is not always possible in the context of a desired pregnancy, understanding strategies that people use to mitigate pain can help providers who may wish to support patients in this context. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: LAW serves as a consultant to AbbVie, Inc.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".