Understanding the phenomenon of sexual desire discrepancy in couples
Bibliographic record
Abstract
Given that desire levels tend to fluctuate over time, discrepancies in sexual desire are an inevitable feature of sexual relationships. However, we know little about how such desire discrepancies relate to a couple's sexual satisfaction. Past studies that have examined the association between sexual desire discrepancy and sexual satisfaction in college/university samples have had inconsistent findings. Also, the results may not generalize to more established romantic relationships. The current study compared two different conceptualizations of sexual desire discrepancy; perceived sexual desire discrepancy was assessed by asking a participant to subjectively compare his/her own level of sexual desire to that of his/her partner. Actual desire discrepancy was computed by subtracting the female partner's score on a self-report measure of sexual desire from the male partner's score on the same measure. In Sample 1, we examined the relationship between actual sexual desire discrepancy and sexual satisfaction for 82 couples in committed long-term relationships. In Sample 2, we investigated the association between perceived sexual desire discrepancy and sexual satisfaction for 191 individuals in committed long-term relationships. Our results showed that higher perceived, but not actual, desire discrepancy was associated with lower sexual satisfaction. In addition, we found that perceived desire discrepancy outcomes differed when measured using different response scales. Findings highlight methodological issues to consider when measuring sexual desire discrepancy and extend the literature by showing that perceived sexual desire discrepancy is associated with sexual satisfaction for couples in committed long-term relationships. Limitations of the current study and implications for future research are discussed.
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 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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".