Domestic Violence Education
Notice bibliographique
Résumé
Domestic violence is one of today's most widespread public health problems, yet primary care providers in the United States1 and Canada2 are consistently identified as being inadequately prepared to routinely confront the issue with their patients. At the University of British Columbia in Vancouver, BC, Canada, second-year medical students in the class of 2001 received nine hours of training in patient screening for domestic violence and management of disclosures. The unit involved lectures, video presentations, patient and expert panels, small-group discussions, and role playing. We sought to evaluate whether these students were able to translate the knowledge they had acquired in the classroom into usable skills in an early clinical training experience. We asked 112 students to volunteer to record their experiences doing domestic violence assessments for adult patients during at least six days in the setting of their mandatory rural family practice elective. Thirty-two students agreed to participate, but only six students submitted completed data forms. This was a surprising and disappointing outcome, especially given the high attendance rate for the domestic violence course and the course coordinators' impression that the education sessions had been extremely well received by the students. A few of the students who withdrew from or refused to participate in the study reported that their preceptors had been opposed to their participating (even though it merely involved the students' recording their own clinical experiences), while others cited lack of time or personal reasons for not participating. Overall, the six students who submitted reports described a very low rate of disclosure in the office setting. Despite these student—participants' initial interest in screening for domestic violence, only one of the six regularly conducted screenings of patients. Of all the patients this one student screened, 38% reported histories of domestic violence. The most common reason the students cited for not screening was that they felt domestic violence was “unrelated to the patient's chief complaint/reason for visit.” Additional barriers to screening identified by the students were that the students “did not feel that it was their position or role to discuss this issue with the patient” as well as a concern about the amount of time required to conduct screening. One student commented on the impact of the education received in the classroom versus the reality of clinical practice: “Following the [educational] sessions, I had thought that I would screen for domestic violence; perhaps I was being unrealistic about the true time pressures and discomfort [that I would experience].” One of the most notable observations was that although all six students reported that their preceptors understood the importance of dealing with domestic violence in the family practice setting, none of the preceptors themselves routinely screened for domestic violence. Preceptor modeling of routine screening practices might have been an effective means of converting class-room-learned practices into comfortable clinical habits. Screening for domestic violence is now a standard of practice.3 We must ensure that domestic violence screening is supported in the clinical teaching setting. Classroom-based education may not be enough to enable students to overcome their discomfort with this topic and with their ability to do domestic violence screening as part of routine practice.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,197 | 0,042 |
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 source (Gemma direct ou Codex distillé), 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 ».