Can Masturbation Regulate PTSD Symptoms? Exploring the Mediating Role of PTSD in Childhood Sexual Abuse and Masturbation Motives
Bibliographic record
Abstract
Childhood sexual abuse (CSA) is a significant public health issue with profound and long-lasting effects on survivors’ emotional, psychological, and sexual well-being. While extensive research has examined the interpersonal sexual challenges associated with CSA, less is known about its association with solitary sexual behaviors such as masturbation, particularly the underlying motives or reasons. This study examined the mediating role of post-traumatic stress disorder (PTSD) symptoms in the relationship between CSA and three specific masturbation motives: mood improvement, relaxation/stress relief, and sexual arousal decrease. A sample of 624 adults (M = 29.51 years, SD = 10.23) completed an online survey assessing CSA history, PTSD symptoms, masturbation frequency, and motives for masturbation. Structural equation modeling (SEM) revealed that PTSD fully mediated the associations between CSA and the three masturbation motives. Specifically, CSA was associated with higher PTSD symptoms, which, in turn, were linked to higher levels of masturbation motives related to mood improvement, relaxation, and sexual arousal decrease. Notably, the direct associations between CSA and masturbation motives were not statistically significant. These findings suggest that masturbation may serve as a coping mechanism—either as adaptive emotional regulation or, at times, as a maladaptive response involving avoidance or 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".