Using causal loop diagrams to develop evaluative research propositions: opportunities and challenges in applications to nature-based solutions - Main article

Oct 26, 2026

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Causal loop diagrams (CLDs) provide an overview of key systemic elements, but they are often used without directly informing empirical evaluations. The authors propose developing systems-informed research propositions—testable causal assumptions emphasizing feedback loops—to guide data collection, hypothesis testing, and interpretation. A qualitative, systems-thinking approach is described, drawing on existing CLDs, published evidence, and expert or stakeholder consultation. The article reflects on applying this method to early stages of two nature-based solution evaluations and shows how CLDs support policy-relevant proposition development.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages27

Reading Time1 h 8 min

AccessFree to download

Abstract

Introduction

The importance of large-scale policy and infrastructure interventions

A different use of the word “evaluate”

Different types of evaluative research questions

MAIN ARTICLE Using causal loop diagrams to develop evaluative research propositions: opportunities and challenges in applications to nature-based solutions Miriam Alvarado,a,b * Jo Garrett,a James Fullam,a Rebecca Lovell,a Cornelia Guell,a Tim Taylor,a Ruth Garside,a Marianne Zandersenc and Benedict W. Wheelera Abstract Causal loop diagrams (CLDs) are often used to provide an overview of important systemic elements related to an issue, rather than to inform empirical evaluations (studies which assess changes following an intervention using observed data) . We suggest that empirical evaluations may beneﬁt from the development of systems-informed research propositions (speciﬁc testable causal assumptions with an emphasis on feedback loops) used to guide subsequent data collection, hypothesis testing and interpretation. We describe a qualitative systems-thinking informed approach building on preexisting CLDs, published evidence, and expert/stakeholder consultation and reﬂect on our experience applying this to the early stages of two nature-based solution (NBS) evaluations. We reﬂect on our experience and suggest that CLDs can be usefully employed to develop systems-informed research propositions to inform subsequent empirical evaluation. This may lead to novel policy-relevant research propositions which differ substantially from effectiveness-oriented (“did it work?”) research questions. Copyright © 2023 The Authors. System Dynamics Review published by John Wiley & Sons Ltd on behalf of System Dynamics Society. Syst. Dyn. Rev. (2023) Introduction The importance of large-scale policy and infrastructure interventions Major challenges (e.g. noncommunicable diseases, climate change) necessitate large-scale interventions that operate within and across complex systems (Raymond et al. , 2017; Rutter et al. , 2017; Seddon et al. , 2020; Skivingtonet al. , 2021) . These are often policy or infrastructure interventions, such as introducing taxes on health and environment-harming products, regulations a European Centre for Environment and Human Health, University of Exeter Medical School, Knowledge Spa, Royal Cornwall Hospital, Truro, UK b MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK c Department of Environmental Science & iClimate – Aarhus University Interdisciplinary Centre for Climate Change, Aarhus University, Roskilde, Denmark * Correspondence to: Miriam Alvarado, MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Box 285 Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK. [E-mail:](E-mail: miriam.alvarado@mrc-epid.cam.ac.uk)[ miriam.alvarado@mrc-epid.cam.ac.uk](E-mail: miriam.alvarado@mrc-epid.cam.ac.uk) Accepted by Krystyna Stave, Received 29 August 2022; Revised 12 May 2023; 17 October 2023 and 15 November 2023; Accepted 21 November 2023 System Dynamics Review System Dynamics Review Published online in Wiley Online Library ([wileyonlinelibrary.com) DOI: 10.1002/sdr.1756](wileyonlinelibrary.com) DOI: 10.1002/sdr.1756) 1 This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. 2 System Dynamics Review mandating cycle lanes and street trees in cities, and investing in large-scale restoration of natural areas. These kinds of interventions often require a conﬂuence of factors, including political will, to align and produce a window of opportunity (Kingdon, 1984) . As such, these interventions are very much not under the control of the researchers who hope to study them. From a research team’s perspective, these interventions are “predetermined,”i.e. determined outside of the scope of the researcher’s inﬂuence. Nevertheless, evaluating these interventions is valuable, as real-worl

FAQs

What do causal loop diagrams (CLDs) typically help with in this work?

CLDs are used to outline key systemic elements related to an issue, providing an overview rather than directly driving empirical evaluations.

How does the article suggest empirical evaluations can benefit from systems thinking?

By developing systems-informed research propositions: specific, testable causal assumptions that highlight feedback loops to structure subsequent data collection, hypothesis testing, and interpretation.

Why may predetermined large-scale interventions be difficult to evaluate with RCTs?

Because researchers generally cannot manipulate or control who receives the intervention, which violates the core premise of randomized controlled trials.

Oct 26, 2026

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