Cultural competency preparedness in medical and health professions students ‐ a collaborative study involving anatomy departments at 20 international universities
Notice bibliographique
Résumé
Introduction Training in cultural competency skills of medical and health professionals has become an important element of school curricula. Evaluation is often performed via self‐assessment among student cohorts within one country. Only a few studies utilize any standardized and validated tests. Little is known about global comparisons of baseline levels of cultural competency preparedness among students in various health professions. The aim of the study is to assess the baseline level of cultural competency preparedness in junior medical and health professions students at 20 universities from around the world, utilizing a previously validated and standardized testing tool. Results from this study will aid medical educators in the assessment of the extent of cultural competency required to be included internationally in health education curricula. Methods 436 medical and students from various health professions students from 20 universities world‐wide participated via an anatomy‐based student exchange program (80% preclinical medical students). The students were given a validated questionnaire (1) to assess their preparedness in reference to cultural competency prior to the start of the program. The students were also asked to self‐evaluate their cultural competency skills on a 5‐point Likert‐type scale (“none” to “a lot”) encompassing different areas of competency (e.g., knowledge, intrapersonal and interpersonal skills, internal and external outcomes, attitudes). Data were analyzed in Excel for statistical analysis stratified by global region ‐ North America (NA), Europe (EUR), United Kingdom (UK), East Asia (EA), and Australia (AUS) Results Data are presented as means ( M) and their standard deviation. The highest self‐assessment mean was for attitudes toward different cultures (4.4 ± 0.7) and lowest for knowledge about other cultures (3.4 ± 0.8). Regarding the question of general preparedness, the average score was 2.93 (± 1.0) in the validated tool (5‐point Likert‐type scale, “very unprepared” to “well prepared”); 4.6% of students felt “very well prepared”, while 24% felt only “well prepared.” A comparison by region showed the highest scores were from NA (3.14 ± 1.1), and the lowest scores from the UK (mean 2.74 ± 0.9). Regarding preparedness to evaluate patients from different cultures, 7% of students felt “very well prepared”, and 24% felt “well prepared”. Comparison between regions showed that the highest scores were found in EUR (3.1± 0.9). Regarding preparedness to treat patients with limited language proficiency, 14% of students felt that they were “very well prepared” (2.6; ± 1.1). A breakdown by regions showed that the highest scores were found in EUR (2.78 ± 1.0). Regarding preparedness to treat patients from ethnic minorities, 17% felt they were “very well prepared”, and 31% felt “well prepared” (3.4 ± 1.1), with the UK scoring highest in this category (3.56 ± 1.1). Discussion Overall, there appears to be a discrepancy among junior students’ self‐assessments of their cultural competency skills and of their preparedness to treat patients, when compared to standardized test results. Cultural preparedness was similar across the evaluated regions. The data reveal that most regions in the world can benefit from cultural competency training for junior medical and health professions students. Reference 1. Green AR, Chun MBJ, Cervantes MC, Nudel JD, Duong JV, Krupat E, et al. Measuring Medical Students' Preparedness and Skills to Provide Cross‐Cultural Care. Health equity. 2017;1(1):15‐22.
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 | 0,012 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».