Using feminist, emotion-focused, and developmental approaches to enhance cognitive-behavioral therapies for posttraumatic stress disorder related to childhood sexual abuse.
Bibliographic record
Abstract
A body of research indicates the efficacy of cognitive-behavioral interventions for the treatment of posttraumatic stress disorder (PTSD) subsequent to sexual assault in adulthood. The generalizability of these treatments to women who present with trauma symptoms associated with childhood sexual abuse (CSA) has yet to be shown, however. A number of characteristics and dynamics of CSA that make it unique from sexual assault in adulthood are described, specifically its disruption of normal childhood development, its impact on attachment style and interpersonal relationships, its inescapability, and the stigma attached to it. Then, drawing on the developmental, emotion-focused, and feminist literatures, a number of considerations that would enhance the application of cognitive- behavioral trauma therapies to the treatment of women with PTSD related to CSA are delineated. These considerations relate to providing clients with corrective interpersonal experiences, creating new relationship events, enhancing affect regulation skills before initiating exposure therapy, considering the time elapsed since the abuse, addressing themes of power, betrayal, self-blame, stigma, and sex-related cognitions and emotions, and helping clients develop a feminist consciousness. (PsycINFO Database Record (c) 2010 APA, all rights reserved).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".