16.E. Workshop: Preventing public health interventions from contributing to social inequalities in health
Notice bibliographique
Résumé
Abstract Reasons Public health aims to improve the health of populations and reduce social inequalities in health, notably through action on social determinants of health, physical and social environments, public policies, access to health services, and community empowerment. As such, public health has a social agenda and therefore a corresponding social responsibility. However, social inequalities in health continue to be a pressing problem in Canada, as well as around the world. Growing research demonstrates that public health interventions can unintentionally contribute to increasing social inequalities in health by perpetuating social norms that stigmatize vulnerable groups, neglecting the needs of vulnerable groups, and/or replicating power dynamics that reinforce situations which disenfranchise vulnerable populations. Objectives This workshop aims to: 1) discuss how public health interventions can inadvertently contribute to increasing social inequalities in health; 2) explore strategies to develop more equitable interventions. Added value Despite growing research on the unintended contributions of public health interventions in increasing social inequalities in health, this pressing problem remains generally under acknowledged in public health research and practice. Yet in order to reverse these effects, researchers and professionals alike need to become aware of and reflect on the potential impacts of their actions on vulnerable populations. Thus, the presentations in this workshop will provide concrete examples based on innovative research findings and critical reflections of the ways in which public interventions can increase social inequalities in health. We will also suggest health equity-related considerations for future intervention evaluation and design. Coherence The two first presentations will serve to illustrate how public health interventions can increase social inequalities in health and how we might reverse these effects by drawing on examples from tobacco control and health care. Based on these examples, the last presentation will demonstrate how a theoretically-driven framework (i.e. Acting Within Contexts) can be applied for intervention evaluation and future equitable intervention design. Format A brief introduction to present the workshop topic and learning objectives (5 minutes) Three presentations by panelists (10 minutes each; 30 minutes total): The unintended effects of tobacco control policies on social inequalities in smoking: Moving forward with a health equity approach; Equality versus equity: Barriers to health care access for Indigenous populations in Canada; Applying the “Acting Within Contexts” framework to intervention evaluation and equitable intervention design. A plenary discussion with the audience to draw collective lessons (25 minutes) Key messages To raise awareness of the potential unintended effects of public health interventions on increasing social inequalities in health. To better understand how to reduce inequities by integrating the needs and contexts of vulnerable populations in intervention planning.
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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 | 0,024 | 0,025 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,007 | 0,004 |
| Science ouverte | 0,003 | 0,009 |
| Intégrité de la recherche | 0,014 | 0,014 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,054 | 0,017 |
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 ».