Bibliographic record
Abstract
OBJECTIVE: To present health care providers with an inclusive, evidence-based framework to identify patients who may benefit from lubricant use during sexual activity, and assist patients in selecting a lubricant tailored to their specific needs. SOURCES OF INFORMATION: A MEDLINE, PubMed, Google Scholar, and Google search was performed for white and grey literature published from 2003 to 2024. Interdisciplinary experts in sexual health also conducted an iterative review. MAIN MESSAGE: Lubricant use during sexual activity has numerous benefits, minimal harms, and can play a role in managing many common sexual health concerns encountered in primary care. However, counselling on lubricant use can be challenging due to a lack of accessible, evidence-based clinical tools. Consequently, clinicians are often hesitant to discuss lubricant use and can only offer anecdotal advice. Lubricant use is especially beneficial for patients using condoms or experiencing dryness, pain (eg, dyspareunia), or dysfunction during sex. There are 3 main types of lubricants available: oil-, silicone-, and water-based products. For patients who use condoms or who experience recurrent vaginal infections or irritation, silicone- or water-based lubricants are recommended, which are free of harmful ingredients and are within recommended osmolality and pH ranges. CONCLUSION: Lubricant use during sexual activity can enhance sexual well-being across diverse patient populations. This review summarizes evidence and provides practical tools to help clinicians integrate counselling on lubricant use into routine sexual health discussions.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".