Perceptions of readiness for interprofessional learning among Ethiopian medical residents at Addis Ababa University: a mixed methods study
Notice bibliographique
Résumé
BACKGROUND: Interprofessional learning is an important approach to preparing residents for collaborative practice. Limited knowledge and readiness of residents for interprofessional learning is considered one of the barriers and challenges for applying Interprofessional learning. We aimed to assess the perceptions of readiness of medical residents for interprofessional learning in Ethiopia. METHODS: We conducted a parallel mixed-methods study design to assess the perceptions of readiness for interprofessional learning among internal medicine and neurology residents of Tikur Anbessa Specialized Teaching Hospital in Addis Ababa, Ethiopia, from May 1 to June 30, 2021. One hundred one residents were included in the quantitative arm of the study, using the Readiness for Interprofessional Learning Scale (RIPLS) tool. All internal medicine and neurology residents who consented and were available during the study period were included. SPSS/PC version 25 software packages for statistical analysis (SPSS) was used for statistical analysis. Descriptive statistics were summarized as mean and standard deviation for continuous data as well as frequencies and percentages to describe categorical variables. Data were presented in tables. In addition, qualitative interviews were undertaken with six residents to further explore residents' knowledge and readiness for IPL. Data were analyzed using a six-step thematic analysis. RESULTS: Of the 101 residents surveyed, the majority of the study participants were male (74.3%). The total mean score of RIPLS was 96.7 ± 8.9. The teamwork and collaboration plus patient-centeredness sub-category of RIPLS got a higher score (total mean score: 59.3 ± 6.6 and 23.5 ± 2.5 respectively), whereas the professional identity sub-category got the lowest score (total mean score: 13.8 ± 4.7). Medical residents' perceptions of readiness for interprofessional learning did not appear to be significantly influenced by their gender, age, year of professional experience before the postgraduate study, and department. Additionally, the qualitative interviews also revealed that interprofessional learning is generally understood as a relevant platform of learning by neurology and internal medicine residents. CONCLUSIONS: We found high scores on RIPLS for internal medicine and neurology postgraduate residents, and interprofessional learning is generally accepted as an appropriate platform for learning by the participants, which both suggest readiness for interprofessional learning. This may facilitate the implementation of interprofessional learning in the postgraduate medical curriculum in our setting. We recommend medical education developers in Ethiopia consider incorporating interprofessional learning models into future curriculum design.
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 | 0,005 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».