Symptoms of depression (not anxiety) mediate the relationship between childhood sexual abuse and compulsive sexual behaviors in men
Bibliographic record
Abstract
OBJECTIVE: Childhood sexual abuse is associated with compulsive sexual behavior, depression, and anxiety in men. Furthermore, both depression and anxiety have been linked to compulsive sexual behaviors. However, whether anxiety and depression mediate the relationship between childhood sexual abuse and compulsive sexual behaviors has yet to be tested. We investigated whether symptoms of depression and anxiety mediate the relationship between childhood sexual abuse and compulsive sexual behaviors in 222 men seeking treatment for such behaviors. METHODS: Participants completed the Sexual Compulsivity Scale, Childhood Trauma Questionnaire, Beck Depression Inventory, and Beck Anxiety Inventory. A cross-sectional parallel mediation analysis was conducted. RESULTS: The prevalence of childhood sexual abuse in our sample was 57%. Significant correlations were found between childhood sexual abuse and compulsive sexual behaviors, depression, and anxiety. The results of the mediation analyses suggested that depression (B = 0.07, standard error [SE] = 0.03, 95%CI 0.02 to 0.15), but not anxiety (B = 0.02, SE = 0.02, 95%CI -0.2 to 0.07), mediated the link between childhood sexual abuse and compulsive sexual behaviors. The pattern of our results remained the same when controlling for other types of childhood trauma. CONCLUSIONS: Depression, not anxiety, appears to mediate the relationship between childhood sexual abuse and compulsive sexual behaviors in men. Future research that tests our mediation analyses using a prospective longitudinal study would be highly informative.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.006 | 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".