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Enregistrement W2906728919 · doi:10.1111/acem.13679

Hot Off the Press: <scp>SGEM</scp> #237. Screening Tool for Child Sex Trafficking

2019· letter· en· W2906728919 sur OpenAlexaff
Christopher Bond, Justin Morgenstern, Corey Heitz, William K. Milne

Notice bibliographique

RevueAcademic Emergency Medicine · 2019
Typeletter
Langueen
DomaineSocial Sciences
ThématiqueSex work and related issues
Établissements canadiensWestern UniversityMarkham Stouffville HospitalUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésMedicineSex traffickingPsychiatrySuicide preventionDepression (economics)Sexual abusePoison controlMedical emergencyCriminologyHuman traffickingPsychology

Résumé

récupéré en direct d'OpenAlex

Child sex trafficking (CST) is a global human rights violation and occurs when a minor is engaged in any sex act that involves an exchange of something of perceived value, whether monetary or nonmonetary.1, 2 Examples of CST include prostitution of children by others, “survival sex” (runaway/homeless children having sex in exchange for shelter or something else needed to survive), working in sex-oriented businesses, or production of child sexual abuse materials.3, 4 Statistics from the United States Human Trafficking Reporting System indicate that 85% of identified sex trafficking victims were U.S. citizens/legal residents and 55% were minors.5 Risk factors associated with CST include a history of abuse, substance use, juvenile justice system involvement, a history of running away from home, and LGBTQ status.6-12 Victims of CST are at risk for a myriad of health-related consequences, including physical injury; chronic pain; sexually transmitted infection (STIs); substance use disorders; and psychiatric disorders such as PTSD, depression, and suicide.13-16 Most of these victims seek medical attention at some point, with 88% having seen a physician during their exploitation.15 This study evaluates a screening tool for CST among pediatric patients who present to a large inner-city emergency department (ED). Children aged 10 to 18 presenting with high-risk chief complaints including many gynecologic and psychiatric complaints or high-risk sexual or social behavior were screened for CST. This was done using a screening tool previously developed from a comparison of CST victims to patients presenting with complaints of acute sexual assault without a commercial component. Overall this was a well-done prospective, observational study performed in the pediatric ED (PED) of a major U.S. city. The sample of patients may not be representative, because it was based on a convenience sample of participants selected during times when the CST investigative team was available in the PED. In addition to this, non–English-speaking patients were excluded and both of these factors did introduce some selection bias. The study attempted to mitigate the selection bias created by convenience sampling through inclusion of a representative sampling of day, evening, night, and weekend shifts. Despite focusing on child trafficking, this study included 18-year-old patients. The authors noted that they were included because they still present to this particular P ED and, upon a positive screen, the CST team would be searching for evidence of CST prior to age 18. A major issue with any study examining sex trafficking is the criterion standard being used. The authors used a federal, legal definition of CST, which is standardized and reproducible. However, it is primarily based on self-report, which means the definition could both overcall and (more likely) under call cases of CST, which would impact the reported sensitivity and specificity. That being said, self-report is likely the best criterion standard available for this diagnosis. External validity is also a limitation of this study, as this was done in an urban inner-city PED, so we are unable to generalize to community EDs. Thankfully, CST is relatively rare. However, small numbers do result in large confidence intervals (CIs) that must be considered when assessing this screening tool. The primary outcome was the diagnostic accuracy of the CST screening tool, which had a sensitivity of 90.9% (95% CI = 58.7%–99.8%), specificity of 53.1% (95% CI = 45.6%–60.4%), positive predictive value of 10.0% (95% CI = 5.0%–17.6%), and negative predictive value of 99.0% (95% CI = 94.7%–99.9%). Other findings revealed that the mean (range) age of CST victims was 15.9 (13–18) years, with nine females and two males. CST victims presented in a variety of social circumstances, including alone, with a parent/guardian, with a friend, with a police officer, and with a social services case manager. A total of 55% of CST victims had seen a medical provider within the past 6 months. History items strongly associated with CST were more likely to have run away from home, have used drugs/alcohol in the past 12 months, have had more than 10 sexual partners, and have had a prior STI. There was no chief complaint among the inclusion criteria that correlated significantly with CST presentation. Although there are some methodologic issues that make us uncertain of the accuracy of this screening tool, CST is an incredibly important topic. This tool is unlikely to be 100% sensitive based on the results presented. However, we expect that CST is frequently missed in current clinical practice, and therefore this screening tool, even if imperfect, may represent a significant improvement for many clinicians. There was very limited social media discussion on this topic, which may be due to its sensitive nature. However, as emergency physicians, we need to be aware of CST and how to screen for it as these patients often present to EDs. We welcome ongoing discussion on The SGEM website. Paper-in-a-pic from Kirsty Challen, @KirstyChallen Child sex trafficking is a high-risk condition with a myriad of health consequences. Emergency physicians are in a unique position to identify victims. The use of a CST screening tool for adolescents presenting to the ED with high-risk complaints might help us identify more at-risk children.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,850
Score d'incertitude au seuil0,214

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0010,000
Communication savante0,0020,002
Science ouverte0,0010,002
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,8500,755

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,054
Tête enseignante GPT0,342
Écart entre enseignants0,288 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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