Diagnosing and Discussing Sexual Abuse: A Scoping Review on Training Methods for Health Care Professionals
Notice bibliographique
Résumé
Fiona Elizabeth van Zyl-Bonk, Sibylle Lange, Antoinette Leonarda Maria Lagro-Janssen, Theodora Alberta Maria Teunissen Department of Primary and Community Care, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, the NetherlandsCorrespondence: Theodora Alberta Maria Teunissen, Department of Primary and Community Care, Research Institute for Medical Innovation, Radboud University Medical Center, Geert Grooteplein 21, Postbus 9101, Nijmegen, 6500 HB, the Netherlands, Tel +31 24 3618181, Email doreth.teunissen@radboudumc.nlPurpose: Sexual abuse is a health issue with many consequences. Recognizing and discussing past sexual abuse has proven to be challenging for health care professionals. To improve overall quality of health care for sexual abuse victims, health care professionals need to be properly trained. The aim of this paper is to provide an overview of training methods for health care professionals and to report on their effectiveness.Methods: A scoping review was conducted. A broad search was executed in six databases in December 2022. Study selection was performed by two independent reviewers, followed by quality assessment and data extraction.Results: After screening of titles and abstracts and later full-text assessment for quality appraisal, seven articles were selected, consisting mostly of non-randomized trials, performed among a total of 1299 health care professionals. All studies were assessed to be of moderate to poor quality. The participants attended training courses with a wide variety of durations, settings, formats and methods. The outcomes showed improvements in self-perceived or measured knowledge, skills and confidence to discuss sexual violence. Changes in clinical practice were scarcely investigated. Training courses were most effective when a mix of didactic passive methods, such as lectures and videos, and active participatory strategies, such as discussions and roleplay, were applied. Timely iteration to reinforce retention of gained knowledge and skills also contributed to effectiveness. Participants most enjoyed incorporating opportunities for receiving feedback in small settings and sharing personal experiences.Conclusion: This scoping review summarizes on how to effectively train health care professionals. Flaws and difficulties in measuring the effectiveness of training courses were discussed. Recognition and discussion of past sexual abuse by health care providers can be effectively trained using an alternating mix of multiple active and passive training methods with room for feedback and personal experiences.Keywords: sexual violence, disclosure, recognition, medical education, post-graduate training
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».