Dental and allied dental students’ cultural climate‐related experiences and perceptions: How does ethnicity/race matter?
Notice bibliographique
Résumé
OBJECTIVES: The cultural climate of an academic institution affects students' academic performance and well-being. The objectives were to investigate the culture-related experiences and perceptions of dental and allied dental students in the United States (US) and Canada who self-identified in response to a survey question as American Indian/First Nation-Indigenous/Hawaiian Native (AI), Black/African American/Canadian American/African (Black), Hispanic/Latinx (HL), Middle Eastern (ME), East Asian/Southeast Asian/South Asian (AA), White/European (White) or multiracial (M). The comparisons focused specifically on experiences of biases/inequities related to systemic factors (policies/practices) and personal discrimination/harassment, and on perceptions of the cultural climate and climate-related consequences, having a sense of belonging and culture-related clinical competence. Relationships between these constructs of interest were explored. METHODS: Descriptive and inferential statistics such as univariate analyses of variance and chi-square tests were used to analyze the data from 10,279 students who participated in the 2022 American Dental Education Association climate study and responded to the question concerning which academic program they attended. RESULTS: AI and Black students reported the highest mean numbers of experienced biases/inequities related to policies/practices, while White students experienced the lowest mean (Range of sum scores: 0-16: AI:5.06/Black:4.38/ME:4.11/M:3.96/HL:3.54/AA:3.47/White:3.06; p < 0.001). The mean sum score of having witnessed and experienced harassment and discrimination was highest for Black and lowest for HL students (Range: 0-4: Black:0.82/M:0.73/ME:0.66/AA:0.6/White:0.46/AI:0.40/HL:0.36; p < 0.001). Significant differences in mean responses were also found for general climate perceptions (5-point answer scale with 5 = most positive: ME:3.58/Black:3.59/M:3.59/AA:3.66/White:3.73/AI:3.77/HL:3.87; p < 0.001), personal climate-related consequences (ME:3.70/BM:3.72/Black:3.73/AA:3.75/AI:3.83/White:3.85/HL:3.96; p < 0.001), having a sense of community (ME:3.84;Black:3.87/AI:3.88/BM:3.93/AA:3.95/HL:4.09/White:4.11; p < 0.001) and the "Culturally competent clinical care" Index (AA:4.30/M:4.32/AI:4.34/Black:4.37/E:4.40/White:4.43/HL:4.54; p < 0.001). The higher the witnessed/experienced harassment/discrimination was, the less positive the students perceived the general climate (r = -0.52; p < 0.001), their own situation (r = -0.51; p< 0.001), their sense of belonging (r = -0.43; p < 0.001) and cultural competence when providing clinical care (r = -0.24; p < 0.001). CONCLUSIONS: Students' ethnic/racial background matters. It affects their perceptions of the school/program climate, their experiences of biases/inequities related to policies/practices and the degree to which they experience and witness harassment and discrimination. These findings should be a wakeup call for faculty and administrators to progress on fulfilling the CODA requirements to create a humanistic environment for all students.
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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 | 0,000 | 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) | 0,002 | 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 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 ».