Exploring Current Practices, Needs, and Barriers for Expanding Distributed Medical Education and Scholarship in Psychiatry: Protocol for an Environmental Scan Using a Formal Information Search Approach and Explanatory Design (Preprint)
Notice bibliographique
Résumé
BACKGROUND Distributed medical education (DME) offers manifold benefits, such as increased training capacity, enhanced clinical learning, and enhanced rural physician recruitment. Engaged faculty are pivotal to DME's success, necessitating efforts from the academic department to promote integration into scholarly and research activities. Environmental scanning has been used to gather, analyze, and apply information for strategic planning purposes. It helps organizations identify current practices, assess needs and barriers, and respond to emerging risks and opportunities. There are process models and conceptual frameworks developed for environmental scanning in the business and educational sectors. However, the literature lacks methodological direction on how to go about designing and implementing this strategy to guide research and practice in DME, especially in the psychiatry field. OBJECTIVE This paper presents a protocol for an environmental scanning that aims to understand current practices and identify needs and barriers that must be addressed to facilitate the integration of psychiatrists from the Dalhousie University Faculty of Medicine’s distributed education sites in Nova Scotia and New Brunswick into the Department of Psychiatry, contributing for the expansion of DME in both provinces and informing strategic planning and decision-making within the organization. METHODS This protocol adopts an innovative approach combining a formal information search and an explanatory design that includes quantitative and qualitative data. About 120 psychiatrists from 8 administrative health zones of both provinces will be invited to complete an anonymous web-based survey with questions about demographics, participants' experience and interest in undergraduate, postgraduate, and continuing medical education, research and scholarly activities, quality improvement, and knowledge translation. Focus group sessions will be conducted with a purposive sample of psychiatrists to collect qualitative data on their perspectives on the expansion of DME. RESULTS Results are expected within 6 months of data collection and will inform policy options for expanding Dalhousie University’s psychiatry residency and fellowship programs using the infrastructure and human resources at distributed learning sites, leveraging opportunities regionally, especially in rural areas. CONCLUSIONS This paper proposes a comprehensive environmental scan procedure adapted from existing approaches. It does this by collecting important characteristics that affect psychiatrists' desire to be involved with research and scholarly activities, which is crucial for the DME expansion. Furthermore, its concordance with the literature facilitates interpretation and comparison. The protocol's new method also fills DME information gaps, allowing one to identify insights and patterns that may shape psychiatric education. This environmental scan's results will answer essential questions about how training programs could involve therapists outside the academic core and make the most of training experiences in semiurban and rural areas. This could help other psychiatry and medical units outside tertiary care establish residency and fellowship programs. CLINICALTRIAL INTERNATIONAL REGISTERED REPORT DERR1-10.2196/46835
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 | 0,160 | 0,193 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,004 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,006 | 0,006 |
| Études des sciences et des technologies | 0,007 | 0,006 |
| Communication savante | 0,006 | 0,006 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,008 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,064 | 0,015 |
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 ».