Beliefs around the causes of inequities and intergroup attitudes among health professional students before and after a course related to Indigenous Peoples and colonialism
Notice bibliographique
Résumé
Abstract Background Addressing the Truth and Reconciliation Calls to Action on including anti-racism and cultural competency education is acknowledged within many health professional programs. However, little is known about the effects of a course related to Indigenous Peoples and colonialism on learners’ beliefs about the causes of inequities and intergroup attitudes. Methods A total of 335 learners across three course cohorts (in 2019, 2020, 2022) of health professional programs (e.g., Dentistry/Dental Hygiene, Medicine, Nursing, and Pharmacy) at a Canadian university completed a survey prior to and 3 months following an educational intervention. The survey assessed gender, age, cultural identity, political ideology, and health professional program along with learners’ causal beliefs, blaming attitudes, support for social action and perceived professional responsibility to address inequities. Pre-post changes were assessed using mixed measures (Cohort x Time of measurement) analyses of variance, and demographic predictors of change were determined using multiple regression analyses. Pearson correlations were conducted to assess the relationship between the main outcome variables. Results Only one cohort of learners reported change following the intervention, indicating greater awareness of the effects of historical aspects of colonialism on Indigenous Peoples inequities, but unexpectedly, expressed stronger blaming attitudes and less support for government social action and policy at the end of the course. When controlling for demographic variables, the strongest predictors of blaming attitudes towards Indigenous Peoples and lower support for government action were gender and health professional program. There was a negative correlation between historical factors and blaming attitudes suggesting that learners who were less willing to recognize the role of historical factors on health inequities were more likely to express blaming attitudes. Further, stronger support for government action or policies to address such inequities was associated with greater recognition of the causal effects of historical factors, and learners were less likely to express blaming attitudes. Conclusion The findings with respect to blaming attitudes and lower support for government social action and policies suggested that educational interventions can have unexpected negative effects. As such, implementation of content to address the Truth and Reconciliation Commissions Calls to Action should be accompanied by rigorous research and evaluation that explore how attitudes are transformed across the health professional education journey to monitor intended and unintended effects.
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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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».