Depression, selective serotonin reuptake inhibitors, and sexual wellbeing in assigned females: exploring the moderating role of sexual flexibility
Bibliographic record
Abstract
BACKGROUND: Depression often causes sexual dysfunction, including reduced desire and pleasure, and selective serotonin reuptake inhibitors (SSRIs), commonly used to treat depression, can worsen these issues, leading to treatment discontinuation. AIM: To examine sexual wellbeing differences across depression and SSRI groups, how depression, SSRI use, and sexual flexibility predict sexual outcomes, and whether sexual flexibility moderates the relationship between sexual functioning, distress, and pleasure. METHODS: Participants (N = 357, mean age 26.8 years) assigned female sex at birth were recruited for an online cross-sectional study. Participants were grouped by SSRI use and depression severity: SSRIs-low depression (n = 86), SSRIs-high depression (n = 117), no SSRIs-low depression (n = 81), and no SSRIs-high depression (n = 73). OUTCOMES: Validated measures of depression, sexual function, sexual distress, sexual flexibility, and sexual pleasure were used. RESULTS: Analyses of variance (ANOVAs) and multiple regressions examined relationships between depression, SSRI use, and sexual wellbeing. Moderation analyses tested whether sexual flexibility moderated the link between sexual functioning, distress, and pleasure. The SSRIs-high depression group reported the poorest sexual wellbeing, while the No SSRIs-low depression group reported the highest. Depression and SSRI use predicted increased sexual distress and decreased functioning, pleasure, and flexibility, explaining 21%-26% of variance. Sexual flexibility moderated the relationship between functioning and pleasure, with stronger effects at lower flexibility levels. CLINICAL IMPLICATIONS: Sexual flexibility may improve sexual functioning and pleasure, providing a positive, adaptable framework for therapy; thus, psychosexual and educational interventions focusing on flexibility could enhance sexual pleasure and reduce distress, fostering sexual resilience and improving relationship dynamics. STRENGTHS AND LIMITATIONS: Strengths include a nuanced analysis of depression severity and SSRI use, offering a comprehensive view of sexual wellbeing. Limitations include reliance on self-reported medication use, inability to assess specific SSRIs, and potential confounding from concurrent antidepressant use. CONCLUSION: SSRIs and depression each uniquely affect sexual functioning, distress, and pleasure, such that those with moderate to severe depression and SSRI use report significantly poorer sexual outcomes.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".