Childhood sexual abuse: community‐based treatment practices and predictors of use of evidence‐based practices
Bibliographic record
Abstract
BACKGROUND: Cognitive behavior therapy with abuse-focused components is empirically supported for children/adolescents who have experienced childhood sexual abuse (CSA). We examined the extent to which community-based psychologists use evidence-based practices (EBP) for CSA and identified predictors of EBP use. METHOD: Psychologists (N = 231) providing CSA treatment services to children/adolescents in Ontario (Canada) were identified through the first census of child and adolescent psychology clinicians registered with the College of Psychologists of Ontario. Participants completed a questionnaire on treatment strategies, sociodemographics, work setting, treatment provision, and attitudes toward EBP. Data were collected between December 2009 and June 2010. RESULTS: The majority (78%) of psychologists providing CSA services reported never having received training in specific treatment approaches for this population. Only 5% of psychologists received training in the EBP of trauma-focused cognitive behavior therapy. Multiple regressions indicated that age, theoretical orientation, continuing education, and attitudes predicted the use of an empirically based intervention for CSA. CONCLUSION: Study findings show that few community-based psychologists have received training in specific treatment approaches for CSA victims and very few are trained to deliver EBP for this population. There are ethical concerns about the practice of psychologists who are untrained and unsupervised doing this work. Research findings, which underline the need for training, supervision, and continuing education, need to be translated into clinical practice.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".