Define and Conquer – Details, episodes & analysis

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Define and Conquer

Science

Frequency: 1 episode/40d. Total Eps: 7

Scientific progress in health psychology is hindered by pervasive issues ranging from the conceptualisation and measurement of our constructs to the formalisation of our theories and organising frameworks. This limited podcast series hosted by Olga Perski and Christoph Bamberg aims to 1) raise awareness of key issues facing the field of health psychology and 2) discuss potential solutions and insights with experts from the newly formed EHPS SIG in Conceptualisation, Formalisation and Measurement and beyond.

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https://doi.org/10.31234/osf.io/wbcn3_v1
2 shares
https://https://doi.org/10.1177/0963721422109648
2 shares
https://doi.org/10.2307/23044045
2 shares

https://cfm.opens.science/
6 shares
https://www.behaviorchange.eu/
2 shares
https://open.lnu.se/index.php/metapsychology/article/view/3638
2 shares

https://harvardonline.harvard.edu/course/causal-diagrams-draw-your-assumptions-your-conclusions
2 shares

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Score global : 63%

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Getting Started on Causal Models and Directed Acyclic Graphs with Louise Poppe

Season 1 · Episode 5

Friday, May 8, 2026 • Duration 44:31

For Episode 5, we invited Louise Poppe to introduce us to causal models, with a particular focus on Directed Acyclic Graphs (DAGs). Together, we discuss why researchers in epidemiology — and, in fact, across many scientific disciplines — can benefit from integrating DAGs into their study workflow. We talk about how to get started with causal thinking, common pitfalls and challenges when building DAGs, and what insights these models can provide for study design, analysis, and interpretation.

This episode offers an accessible introduction to causal thinking with DAGs and is a great opportunity to expand your methodological research toolbox.

If this episode sparked your interest and you would like to explore the topic further, here are some helpful resources

Poppe, L., Steen, J., Loh, W. W., Crombez, G., De Block, F., Jacobs, N., ... & Paepe, A. L. D. (2025). How to develop causal directed acyclic graphs for observational health research: a scoping review. https://doi.org/10.1080/17437199.2024.2402809
Poppe, L., De Paepe, A. L., Deforche, B., Van Dyck, D., Loeys, T., & Van Cauwenberg, J. (2025). Experience sampling method studies in physical activity research: the relevance of causal reasoning. https://doi.org/10.1186/s12966-025-01723-w
Rohrer, J. M. (2018). Thinking clearly about correlations and causation: Graphical causal models for observational data. https://doi.org/10.1177/251524591774562
Online Harvard EdX course by Hernán: https://harvardonline.harvard.edu/course/causal-diagrams-draw-your-assumptions-your-conclusions
Hernán MA, Robins JM (2020). Causal Inference: What If. Causal Inference: What If (the book) — Miguel Hernán
Tennant, P. W., Murray, E. J., Arnold, K. F., Berrie, L., Fox, M. P., Gadd, S. C., ... & Ellison, G. T. (2021). Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations. https://doi.org/10.1093/ije/dyaa213

Define and Conquer – Details, episodes & analysis

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Define and Conquer – Details, episodes & analysis

Podcast details

Recent rankings

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Shared links between episodes and podcasts

DOI Foundation17

Other10

Harvard1

RSS feed quality and score

Publication history

Latest published episodes

Similar podcasts and content

Related Shows Based on Content Similarities

Related Shows Based on Content Similarities

DOI Foundation17

Other10

Harvard1

Apple Podcasts

Spotify