Alexithymia is associated with greater sexual distress among women and men
Bibliographic record
Abstract
The ability to recognize, communicate, and regulate emotions and bodily sensations is integral to sexual function. Consequently, individuals higher in alexithymia—characterized by difficulties identifying and describing emotions—have increased vulnerability to problems with their sexual function as well as sexual dysfunction. Despite established links between alexithymia and sexual function difficulties, there is limited research examining links between alexithymia and sexual distress in women and no studies in men. This is surprising given that sexual distress is a necessary criterion for diagnosing sexual dysfunction. The aim of the present study was to examine (a) associations between alexithymia and sexual distress in women and men and (b) which facets of alexithymia are most relevant to sexual distress. In Study 1, higher levels of alexithymia were positively associated with greater sexual distress in a community sample of women ( n = 138) and men ( n = 140). In Study 2, difficulty identifying feelings was the only facet of alexithymia significantly linked to sexual distress in an undergraduate sample of women ( n = 398) and men ( n = 88). In both studies, individuals with clinically significant sexual distress reported significantly greater alexithymia relative to those below clinical distress thresholds. Consistent with theories of emotion recognition and regulation, difficulty identifying feelings may inhibit subsequent emotion regulation processes that are crucial for modulating negative emotions associated with sexual difficulties. This study suggests that alexithymia is associated with greater sexual distress and that improving emotional identification may be beneficial for individuals experiencing sexual distress.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".