What Measures are Effective in Trauma Screening for Young Males in Custody? A COSMIN Systematic Review
Bibliographic record
Abstract
Despite the available evidence identifying the high prevalence rates of potentially traumatic experiences in forensic populations, there is still a lack of evidence supporting the use of suitable assessment tools, especially for young males in custody. For services to identify, support, and offer trauma interventions to this cohort, practitioners require reliable and valid assessment tools. This systematic review (Open Science Framework registration: https://osf.io/r6hbk) identifies those tools able to provide valid, reliable, and comparable data for this cohort. Five electronic databases and gray literature were searched to identify relevant measures. Inclusion criteria: studies of tools to assess for trauma with males aged between 12 and 25 years-old in a custodial setting, any year of publication, and available in English. Exclusion criteria: studies that did not measure psychological trauma or include a standalone trauma scale, or report primary data. A three-step quality assessment method was used to evaluate the methodological quality and psychometric properties of the measures. Fourteen studies were selected for review (which included 12 measures). The studies sampled a total of approximately 1,768 male participants and an age range of 12 to 25 years. The studies reported on various types of psychometric evidence and due to the lack of homogeneity, a narrative synthesis was used to discuss, interpret, and evaluate each measure. The overall quality of the psychometric properties of the measures in this review showed that the currently available instruments for the assessment of trauma with young males in custody is limited but promising.
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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 | 0.023 | 0.125 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".