(PM-18) EXPLORING THE CONNECTIONS BETWEEN HYPERSEXUALITY AND SEX HORMONE: A PRELIMINARY STUDY IN BRAZILIAN MEN
Bibliographic record
Abstract
Abstract Introduction Compulsive sexual behavior disorder (CSBD) or hypersexual behavior has gained global attention due to its adverse impact on health. However, there is just a few data on sex hormones of people reporting CSBD/hypersexual behavior. Objective Here, we investigate correlations between CSBD/hypersexual behavior and sex hormone in a sample of 34 Brazilian men who met the diagnostic criteria for CSBD/hypersexual disorder. Methods After ethical approval, participants provided informed consent and were assessed through the Instrument of Investigation of CSBD Diagnostic Criteria – ICD11, Hypersexual Disorder Screening Inventory (HDSI), Compulsive Sexual Behavior Inventory (CSBI), Sexual Compulsivity Scale (SCS), and Childhood Trauma Questionnaire (CTQ). Additionally, participants' basal blood levels were evaluated. Results The sample had a mean age of 38.2 years (SD ± 10.05). The median hormone levels of total testosterone 484 ng/dL [356;560], free testosterone 372 pmol/L [285;472], prolactin 9.50 ng/mL [8.30;13.4], estradiol 23.9 pg/mL [23.9;27.5], SHBG 26.7 nmol/L [21.8;33.5], FSH 4.10 IU/L [2.8;5.3], and LH 2.90 IU/L [2.18;3.85]. Mean scores for HDSI, CSBI, SCS, and CTQ were 23.2 (SD ± 3.80), 66.3 (SD ± 8.26), 33.7 (SD ± 4.14), and 37.6 (SD ± 8.03), respectively. Spearman's correlation analyses showed a positive correlation between total with free testosterone levels (Rho: 0.87); Total testosterone levels with SHBG (Rho: 0.59); a negative correlation between total and free testosterone levels with SCS score (Rho: –0.38; Rho: –0.35, respectively); a negative correlation between LH levels and CTQ total scores (Rho: –0.63); a negative correlation between CSBI with SCS scores (Rho: –0.58). Conclusion Our data shows the first exploration between hypersexuality and sex hormones in a Brazilian men sample, supporting previous findings about a relationship of testosterone levels with SCS scores in hypersexual individuals. Financing FAPESP.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".