Workshop: Behaviour change and knowledge translation: The unlocked potential to improve people’s health
Notice bibliographique
Résumé
Abstract Background Despite the complexities of modern healthcare it remains the case that human behaviour plays a critical role in health outcomes and in the efficacy of most treatments. We know that people get sick because of unhealthy behaviours. We know that the success of most healthcare interventions is highly dependent on patients’ willingness to adhere to self-care activities such as taking medications or performing self-examinations. Over the last decades well-validated, cost-effective behavioural medicine interventions have been developed. The field has contributed to strategies in health education, with techniques for modifying behaviour, and enhancing motivation and learning for health. More recently, multilevel intervention models, including environmental and policy variables, are being increasingly proposed and tested. Yet, for several reasons, only few such interventions have been translated into policy recommendations or implemented successfully in clinical practice. Through highlighting critical gaps in knowledge translation that can be addressed by integrating modern theoretical and methodological approaches across disciplines we hope to contribute to the development of effective and implementable behaviour change interventions for optimal population and individual health and well-being. Aim The aim of this workshop is to broaden our understanding of measures that have originated from behavioural sciences and have a lot to offer to public health. This workshop also seeks to contribute to capacity building in knowledge translation and evidence-informed decision-making in public health. Workshop structure The workshop will consist of five presentations providing an overview of topical issues in the field of behaviour change and knowledge translation, followed by an interactive audience discussion. The first presentations will introduce the most recent challenges in knowledge translation from the WHO/Europe perspective. The second presentation will discuss the possibilities of using behaviour change principles in the development and adoption of health policies showcasing the Canada’s newly adopted Food Guide. The third presentation will highlight the challenges in tackling physician’s ability to effectively conduct behaviour change counselling with their patients in the context of chronic disease prevention. The fourth presentation will make the link between the knowledge translation theory and practice, using the Behaviour Change Wheel theory. The fifth presentation will introduce the free academic meta-search engine - Motrial, which has a great potential in evaluating the randomized controlled trials and fuelling meta-analyses and systematic reviews in return of better quality. Further to the reflexion on the current knowledge base, an audience discussion will give attendees the opportunity to share their opinions regarding challenges and opportunities in knowledge translation to improve people’s health and well-being. Key messages Policy development and adoption can be considered as a behaviour change process. The application of behaviour change principles to the policy process may lead to greater stakeholder engagement and faster policy implementation.
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 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 | 0,046 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,004 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,012 | 0,009 |
| Science ouverte | 0,006 | 0,019 |
| Intégrité de la recherche | 0,015 | 0,024 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,042 | 0,015 |
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 ».