Neurophysiological impact of childhood sexual abuse in men: A diffusion tensor imaging study
Bibliographic record
Abstract
BACKGROUND: Childhood sexual abuse (CSA) can cause lasting neurodevelopmental changes, posing significant challenges for survivors. Its specific impact on men remains heavily stigmatized and under-researched. This study examined neurophysiological correlates of CSA in men using diffusion tensor imaging (DTI). METHODS: A community-based sample of men with CSA histories (n = 15) and controls (n = 13) were recruited from urban centers across Canada. All participants underwent DTI, which measures white matter integrity through fractional anisotropy (FA) values. Group comparisons were conducted using whole-brain voxel-wise and post-hoc region-of-interest (ROI) analyses with Bonferroni correction. Effect sizes (Cohen's d) and power were reported. RESULTS: Compared to controls, the CSA group showed significantly lower FA values in the right posterior cingulum (d = 1.28, p = 0.002), superior frontal gyrus (d = 1.13, p = 0.006), anterior thalamic radiation (d = 1.19, p = 0.004), and superior longitudinal fasciculus (d = 1.90, p < 0.001). These differences remained significant after Bonferroni adjustment. Lower FA values were also observed in the left anterior cingulum and right forceps minor, though these did not meet adjusted significance thresholds. CONCLUSIONS: This study provides empirical evidence of the long-lasting neurophysiological impact of CSA in men. The observed white matter differences may underlie the behavioral, emotional, and cognitive difficulties often experienced by this population. These results are discussed in the context of destigmatizing male CSA and helping clinicians better understand the neurophysiological factors affecting their patients.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".