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Enregistrement W4389064182 · doi:10.4103/efh.efh_309_23

Co-editors’ Notes

2023· editorial· en· W4389064182 sur OpenAlexaboutno aff
Payal Bansal, Danette McKinley, Michael Glasser

Notice bibliographique

RevueEducation for Health · 2023
Typeeditorial
Langueen
DomaineHealth Professions
ThématiqueInterprofessional Education and Collaboration
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésDisadvantageHealth careEquity (law)Public relationsPolitical scienceMedical educationMedicine

Résumé

récupéré en direct d'OpenAlex

Welcome to the second issue of the year of Education for Health (EfH)! As always, we bring to you an assortment of articles that include Original Research, Practical Advice, General Articles, Student Contributions, and Letters to Editors from various countries, encompassing a range of important issues from policy to ground level implementation. The papers provide interesting research insights, share successes, and implementation challenges in healthcare and education of health professionals that eventually inform practice for better health outcomes. Increasing equity in admissions to health professions programs is an international challenge. In their article titled “Preparing for Medical School Selection: Exploring the Complexity of Disadvantage through Applicant Narratives,” Jackson et al. identify the factors that facilitate the application process. Social capital is important and their work identifies how some applicants are using limited resources to accumulate experiences they believe will increase their likelihood of acceptance, despite efforts to create equitable admissions practices. They use a unique lens, bricolage, to discuss how applicants approach these challenges. They encourage changes in admissions practices to determine whether the traits of “bricoleurs” might be desirable for admissions. Research shows that interprofessional education enables collaborative care, with improved patient outcomes. Gilbert et al. in their original research article bring together the experiences from six countries to highlight the need for a global policy to implement interprofessional education for collaborative practice (IPECP). The authors present an interesting synthesis of case studies describing policy initiatives from Canada, Germany, Thailand, Philippines, Uruguay, and India about IPECP implementation and challenges faced. They envisage research-based evidence to inform policy thus facilitating effective implementation of IPECP and eventual inclusion in global accreditation standards. Clithero et al. report on the use of a qualitative analysis process, parallaxis praxis, which integrates arts into the data collection. This methodology was used to explore the students’ understanding of social accountability. Both the topic and the methods used are intriguing, and the study demonstrates how the use of art in data collection might be used to explore how concepts are operationalized for individuals. Exploring meaning in this way encourages interaction and reflection. Exploring the meaning of social accountability in this way allowed participants to develop a deeper meaning of the concept. Chhabra et al. approach social accountability from a different viewpoint. In the brief communication, “Social Responsiveness: The Key Ingredient to Achieve Social Accountability in Education and Health Care,” the role of compassion in providing care and social accountability is discussed. Screening for this characteristic in admissions is one approach. Ensuring that the “hidden curriculum” engenders and emphasizes the importance of compassionate care is another. In another article on expanding opportunities for historically minoritized applicants to medical school, Oguntula et al. report on a program-supporting applicants by preparing them for the computer-based assessment for sampling personal characteristics test. Barriers identified included access to health-care professionals for mentoring and, once again, the pandemic offered a way to increase access. By using an online platform, the innovation allowed collaboration between medical students and medical school applicants. Those with similar lived experiences were able to mentor those applying and support their application process. Reducing financial burdens and building social capital were two important, positive outcomes of this work. Training programs widely employ Kirkpatrick’s model for program evaluation. In their practical advice paper, Sabey et al. describe a modified design in the context of a research methodology training program that includes the individual, organization, and health system. The framework provides a structure encouraging a continuous approach to program evaluation that allows the planning of evaluation activities at the very outset rather than later. It can be adapted to other training programs as well. One letter to the editor in this issue explores the importance of disclosure of medical errors by physicians and its impact on their mental health, advocating support to help them cope, and early learning for students using simulation. In a second letter the author, having held multiple academic roles in his career, shares his “eye opening experience” of completing a medical education fellowship and learning curriculum development formally for the first time. We hope these articles provoke your thinking about health workforce education and motivate you to share your experiences and research through EfH.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,009
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Études des sciences et des technologies, Charge 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: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,095
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,009
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0020,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,005

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 Opus0,049
Tête enseignante GPT0,552
Écart entre enseignants0,502 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

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

En bref

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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