Bibliographic record
Abstract
Human trafficking is a global public health crisis catastrophically threatening the health and well-being of those trafficked. Limited studies measure health care providers’ confidence in their ability to recognize, treat, and refer those being trafficked. This integrative review synthesizes current knowledge on human trafficking and identifies gaps in research on educational interventions aimed at increasing provider knowledge and awareness as well as confidence in treating and referring those being trafficked. A systematic search of five databases identified peer-reviewed published papers between 2015 and 2021. The integrative review followed the framework of Toronto and the systemic search was guided by the Preferred Reporting Items for Systematic Revies and Meta-Analyses (PRISMA). Melnyk’s Levels of Evidence framework was used for appraising the quality of evidence. Findings across studies (N = 11) reveal that providers (nurses, doctors, social workers, and hospital staff) have low knowledge and confidence in their knowledge surrounding human trafficking and their role in identification, treatment, and referrals related to an array of barriers. Further findings across studies (N = 13) reveal that providers’ knowledge and confidence knowledge about human trafficking and identification, and referral of those being trafficked increased significantly with an array of educational interventions, but the transfer of this new knowledge to practice is a gap in research, as few studies reported this (n = 2).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".