Comparison Between Male and Female Survivors of Sexual Abuse and Assault in Relation to Age at Admission to Therapy, Age of Onset, and Age at Last Sexual Assault: Retrospective Observational Study
Bibliographic record
Abstract
BACKGROUND: Sexual abuse and sexual assault are complex phenomena that involve many factors (or correlates) and have many health and financial implications for individuals, families, and society. Every correlate needs to be studied in detail, individually and in relation to other correlates. Only with a thorough understanding of these correlates can more efficient and targeted prevention and intervention programs be designed. OBJECTIVE: The purpose of this study was to examine the differences between male and female survivors of sexual abuse and sexual assault regarding the correlates of the survivors' age of onset of assault, age at the last assault, and age at which they entered therapy. METHODS: Therapists at eight sexual assault centers in the province of Alberta, Canada, completed a questionnaire on each of their clients over a period of 7 years. A total of 3302 participants, of whom 2901 (87.86%) were female and 401 (12.1%) were male survivors of sexual abuse and assault, were included in this study. Mostly descriptive analyses were carried out on the 4 variables of concern in this study. RESULTS: Regarding the number of survivors who sought therapy, female survivors outnumbered male survivors by a ratio of 7:1, with different ratios for different age groups. As children age, their risk of being sexually assaulted for the first time decreases. Male children are more likely to be sexually abused at a younger age, whereas female children are more vulnerable to being assaulted at all ages, particularly in adolescence. The mean age of onset of sexual abuse was found to be 6.71 (SD 2.86) years, and the odds of experiencing the first sexual assault during childhood, as opposed to adolescence, were 4:1 for females and 9:1 for males. Male survivors were two times more likely than female survivors to experience their first sexual assault in childhood. The vast majority of survivors sought help many years after being sexually assaulted, and male survivors waited an average of 3 years longer from the last sexual assault before seeking therapy. CONCLUSIONS: The majority of survivors of sexual abuse and sexual assault live with the consequences for many years before they seek help, and a large proportion of male survivors are not likely to seek help.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".