Patients and students co‐develop a resource database
Notice bibliographique
Résumé
BACKGROUND: Health professional students are provided with a wealth of online learning resources recommended by curriculum developers or instructors, the majority of which focus on biological and clinical science. Our goal was to develop a database of learning resources to help students and faculty members understand chronic health conditions from a patient's perspective. Resources were recommended by patients and evaluated by students. Our goal was to develop a database of learning resources … recommended by patients and evaluated by students METHODS: Patients and caregivers who recommend resources to their students in an interprofessional health mentors programme, and participants in a Disability Learning Resource planning session, provided 68 different resources, ranging from community organisation websites to personal biographies. Resources were organised into eight categories and rated by 10 senior health professional students. Patients … provided 68 different resources, ranging from community organisation websites to personal biographies RESULTS: Patients recommended resources so that students could learn what it is like to live with a particular condition, and also learn about useful patient information resources and community-based advocacy organisations. Students identified 40% of the rated resources as useful or exceptionally useful, and identified the characteristics of useful and not useful resources. Students identified 40% of the rated resources as useful or exceptionally useful … CONCLUSIONS: Students want resources that are easy to navigate and are well organised. They want a 'one-stop shop' to access information about a particular condition or disease, and value resources that they can recommend to their patients as well as use to expand their own knowledge. Students value information about local organisations for specific conditions that they can connect their patients to, and from which they may learn more about existing support initiatives in their communities. Clinical educators could better prepare students for practice by making available patient-recommended resources. Students … value resources that they can recommend to their patients as well as use to expand their own knowledge Students value information about local organisations for specific conditions that they can connect their patients to … Clinical educators could better prepare students for practice by making available patient-recommended resources.
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 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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,002 |
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 ».