The good student or the good patient? The barriers encountered by undergraduate medical students with disabilities at the Northern Ontario School of Medicine
Notice bibliographique
Résumé
The American Association of Medical College’s (AAMC) Lived Experience report was released \nin March 2018 with hopes of broadening the diversity of medical students to include more of \nthose with disabilities (Meeks & Jain, 2018). The authors hoped to generate discussion and study \nthe lived experiences of current medical students, residents and practicing physicians with \ndisabilities to learn about the barriers and supports that they have and continue to encounter \nalong their journeys in medicine. In response to the Meeks & Jain (2018) publication, the \npurpose of this study was to replicate their study with the research question “What are the \nbarriers encountered by undergraduate medical students with self-identified disabilities at one \nNorthern Ontario medical school?”. The Lived Experience Project provides a unique opportunity \nto learn about, and compare the experiences of, participants in this study to medical students at \none medical school in Northern Ontario (Meeks & Jain, 2018). In doing so, the climate and \nculture of this school and how this affects the treatment and education of students with \ndisabilities, including the barriers they face in the academic accommodation process, in medical \nenvironments and throughout medical school as a whole were explored. \nA qualitative descriptive study design was used. Data was collected using an initial \ndemographics-based survey followed by a semi-structured interview. Interviews were conducted \nin person or by telephone. Data was transcribed and analysed using Braun & Clarke Thematic \nAnalysis (2013). It was found that the participants of this study found barriers directly associated \nwith their medical education in addition to barriers indirectly associated with their medical \neducation and finally, barriers outside of medical school. Supports in the lives of participants \nwere also identified as a theme in the current research, suggesting a positive impact in the lives \nof medical students with disabilities. No barriers specific to being a student in Northern Ontario \narose, which may be in part to the nature of the sample and small sample size. Implications for \nthis research include reviews of accommodation policies, revision of technical standards at a \nnational and institutional level as well as strengthened communication between the student, the \nmedical school, faculty, and administration.
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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 | 0,000 | 0,000 |
| 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 | 0,001 | 0,003 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».