Child sexual abuse and the development of psychiatric disorders: a neurobiological trajectory of pathogenesis
Bibliographic record
Abstract
Child sexual abuse (CSA) is an important public health problem with long-standing neurobiological, developmental, and psychiatric abnormalities. The present review analyzes the long-term effects of CSA from a developmental, psychiatric morbidity, neurochemical and neurobiological perspective and then tries to posit a developmental neurobiological trajectory from CSA to the genesis of psychopathology in later life. The role of various neurotransmitters such as serotonin and dopamine affected by CSA are discussed. Serotonin abnormalities have been reported in various studies among participants exposed to CSA. Structures such as the prefrontal cortex, superior temporal gyrus, corpus callosum, parietal lobes, hippocampus, and cerebellum all demonstrate volumetric and structural changes in response to the trauma of CSA. Neurocognitive studies demonstrate memory and spatial awareness as well as decrements in general cognitive performance and memory when compared to normal individuals. The hypothalamic-pituitary-adrenal axis has also been implicated in CSA, and there is an alteration in corticotropin-releasing hormone response due to the continuous cumulative trauma of CSA. This paper also reviews a section on the role of genetic and epigenetic factors in the development of psychiatric disorders as a result of exposure to episodes of CSA where studies have demonstrated changes in DNA methylation in response to CSA. This review tries to hypothesize a developmental trajectory framework which is individual for every case where exposure to CSA may lead to psychopathology and psychiatric morbidity later in life. Rapid and emerging fields such as developmental traumatology in relation to CSA are also discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".