How are sexual frequency and relationship satisfaction intertwined? A latent profile analysis of male–female couples.
Bibliographic record
Abstract
Do most couples who report high sexual frequency also report high relationship satisfaction? Are there happy sexless couples? In this study, we take a novel approach to investigating how sexual frequency and relationship satisfaction are intertwined by using latent profile analysis to identify subgroups of couples based on how frequently the couple has sex/sexual intercourse and the relationship satisfaction of both partners. We also test how demographic (age, relationship duration, raising young children) and relational (commitment, self-disclosure, conflict) covariates are associated with profile membership. Data came from 2,101 male-female couples (82.7% of males and 95.8% of females were young adults between the ages of 20-39 years) in the German Family Panel (pairfam) study. Results revealed that couples were classified into four distinct profiles. The majority of the sample (86.38%) occupied a profile in which both partners were highly satisfied and the couple had sex frequently (just less than once a week). The second profile was characterized by low relationship satisfaction for both partners and infrequent sex (less than 2-3 times per month; 3.60%). Two profiles had partners with discrepant levels of relationship satisfaction and a moderate sexual frequency (between two and three times per month and weekly): a satisfied female partner and highly dissatisfied male partner profile (4.01% of the sample) and a satisfied male partner and dissatisfied female partner profile (6.01%). The demographic covariates were rarely associated with class membership, but the relational covariate associations were robust. Couples with infrequent conflict and high levels of self-disclosure and commitment from both partners had higher odds of being in the highly satisfied and frequent sex profile compared to all other profiles. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".