A Critical Discourse Analysis of Risk for Preventing Type 2 Diabetes from Primary Care Provider, At-Risk Patient, and Canadian Policy Perspectives
Notice bibliographique
Résumé
Global estimates suggest over 1.3 billion individuals will be living with diabetes by 2045, of which up to 96% of cases are type 2 diabetes (T2D), a disease that may be prevented or delayed. This research program explored the discourses of risk for T2D to understand how language use shapes how we come to understand, know (or not know) about risk for the disease, and the effect on how we are willing to prevent the disease. This research program consisted of three studies through the lens of: 1) primary care providers; 2) at-risk patients; and 3) Canadian policy. Foucauldian discourse analysis was applied utilizing thematic analysis to understand the discourses of risk for T2D. Study 1 included semi-structured interviews with primary care providers (n=14) working in a family health team. Findings suggest providers use the ‘prediabetes’ threshold to open up risk and preventative discourses but this can also delay communicating about risk for the disease until the threshold is reached. Study 2 included two focus groups and two interviews with patients who were told by a provider they were at a high-risk or had prediabetes. Findings suggest that patients use prediabetes to navigate their attendance to risk for the disease, but struggle with their understanding of the clinical purpose of prediabetes and how to reduce their risk for the disease. Study 3 included a discourse analysis of policy texts and the current Framework for Diabetes in Canada (n=7). Data were analyzed deductively through application of Carol Bacchi’s ‘what’s the problem represented to be’ framework. Findings suggest the problem of risk for T2D is represented as Canadians not being aware of risk factors for the disease and needing to be screened, identified, and educated about the risks for the disease. This was problematized as an individual’s problem to deal with their risk of T2D, rather than attending to the social and environmental conditions which create and maintain the risk. With rates of T2D expected to continue to increase in the future, there is a need to consider how language governs what we are willing to do to address risk for T2D.
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Comment cette classification a été obtenuedéplier
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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».