An ecological analysis of child sexual abuse disclosure: considerations for child and adolescent mental health.
Bibliographic record
Abstract
OBJECTIVES: Research continues to indicate a concerning number of children and youth, between 60-80%, withhold disclosure until adulthood suggesting that many children endure prolonged victimization or never receive necessary intervention. The study aim was to qualitatively identify factors that impede or promote child sexual abuse (CSA) disclosure. METHODS: Using a phenomenological design, forty adult survivors of CSA were interviewed about their disclosure experiences to provide retrospective accounts of their childhood and adolescent abuse experiences, disclosure attempts, and meaning-making of these experiences. RESULTS: Findings show that disclosure is multiply determined by a complex interplay of factors related to child characteristics, family environment, community influences, and cultural and societal attitudes. An ecological analysis is offered to understand these complexities. Unless barriers to disclosure are eradicated, negative effects of CSA can persist manifesting in serious mental health issues. CONCLUSIONS: Practitioners can expect to work with children, adolescents and adults who have withheld disclosure or attempted to tell over time having experienced a wide range of responses. Multi-level intervention is recommended at the individual, community and macro-levels. Future investigations should focus on how to identify and measure the impact of community and macro level factors on disclosure, aspects that have received much less attention.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".