Whose burden? A comprehensive approach to describing burden of disease by synthesizing evidence from diverse perspectives
Notice bibliographique
Résumé
Epidemiologists tasked with addressing public concerns about a specific health issue and developing effective public health strategies aimed at reducing related health risks must begin by describing the extent of the health threat in the target population. Typical approaches use quantitative measurement of pertinent epidemiologic indicators to assess the impact of the health threat. To ensure that public health strategies developed through the investigative process are relevant to the target population, however, public health researchers can gain valuable insights by also ascertaining how affected members of the target population view the health issue and related risks. While existing literature espouses the benefits of building collective knowledge to capture the depth and complexity of health and disease, there is limited information on the most effective ways to synthesize different forms of evidence to construct a comprehensive assessment of the burden of disease. Indigenous communities in the Northwest Territories and Yukon concerned about their high prevalence of Helicobacter pylori infection and the associated risk of stomach cancer are currently guiding research that addresses their concerns. In this dissertation, I report research I conducted as part of this community-driven research program to characterize the self-described impact of disease by individuals at risk and describe disease burden using more conventional epidemiologic approaches. I then describe the similarities and differences in disease burden assessed using diverse forms of evidence and synthesize this information to provide a comprehensive description of disease burden among those impacted. My synthesis confirmed a disproportionate impact of H. pylori infection and associated diseases among northern Indigenous populations compared to other groups. However, academic, healthcare, and community research partners did not appear to have a shared understanding of H. pylori and its impacts; furthermore, the burden attributed to H. pylori infection by northern community members may be broader than the burden as described by academic scientists and healthcare providers. In addition to these contributions, this dissertation provides examples of best practices when using epidemiologic approaches to describe disease burden, particularly when community concerns about a specific health issue trigger investigations. Using examples of community-academic collaborations that identify and implement reciprocal learning initiatives and incorporate the target population’s characterizations of the health problem, this work highlights the importance of building shared knowledge about a health issue of interest. Ultimately, this dissertation illustrates the value of incorporating diverse perspectives when seeking effective public health solutions.
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 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 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».