Workshop: Behaviour change and knowledge translation: The unlocked potential to improve people’s health
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.046 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.006 | 0.019 |
| Research integrity | 0.015 | 0.024 |
| Insufficient payload (model declined to judge) | 0.042 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".