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Modelling decay in effectiveness for evaluation of behaviour change interventions: a tutorial for public health economists

Author

Listed:
  • Paolo Candio

    (University of Birmingham
    University of Oxford)

  • Koen B. Pouwels

    (University of Oxford)

  • David Meads

    (Leeds Institute of Health Sciences, University of Leeds)

  • Andrew J. Hill

    (Leeds Institute of Health Sciences, University of Leeds)

  • Laura Bojke

    (University of York)

  • Claire Williams

    (University of Oxford)

Abstract

Background and purpose Recent methodological reviews of evaluations of behaviour change interventions in public health have highlighted that the decay in effectiveness over time has been mostly overlooked, potentially leading to suboptimal decision-making. While, in principle, discrete-time Markov chains—the most commonly used modelling approach—can be adapted to account for decay in effectiveness, this framework inherently lends itself to strong model simplifications. The application of formal and more appropriate modelling approaches has been supported, but limited progress has been made to date. The purpose of this paper is to encourage this shift by offering a practical guide on how to model decay in effectiveness using a continuous-time Markov chain (CTMC)-based approach. Methods A CTMC approach is demonstrated, with a contextualized tutorial being presented to facilitate learning and uptake. A worked example based on the stylized case study in physical activity promotion is illustrated with accompanying R code. Discussion The proposed framework presents a relatively small incremental change from the current modelling practice. CTMC represents a technical solution which, in absence of relevant data, allows for formally testing the sensitivity of results to assumptions regarding the long-term sustainability of intervention effects and improving model transparency. Conclusions The use of CTMC should be considered in evaluations where decay in effectiveness is likely to be a key factor to consider. This would enable more robust model-based evaluations of population-level programmes to promote behaviour change and reduce the uncertainty surrounding the decision to invest in these public health interventions.

Suggested Citation

  • Paolo Candio & Koen B. Pouwels & David Meads & Andrew J. Hill & Laura Bojke & Claire Williams, 2022. "Modelling decay in effectiveness for evaluation of behaviour change interventions: a tutorial for public health economists," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(7), pages 1151-1157, September.
  • Handle: RePEc:spr:eujhec:v:23:y:2022:i:7:d:10.1007_s10198-021-01417-7
    DOI: 10.1007/s10198-021-01417-7
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    References listed on IDEAS

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    1. Miqdad Asaria & Susan Griffin & Richard Cookson, 2013. "Distributional cost-effectiveness analysis: a tutorial," Working Papers 092cherp, Centre for Health Economics, University of York.
    2. Eline M. Krijkamp & Fernando Alarid-Escudero & Eva A. Enns & Hawre J. Jalal & M. G. Myriam Hunink & Petros Pechlivanoglou, 2018. "Microsimulation Modeling for Health Decision Sciences Using R: A Tutorial," Medical Decision Making, , vol. 38(3), pages 400-422, April.
    3. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    4. Candio, Paolo & Meads, David & Hill, Andrew J. & Bojke, Laura, 2020. "Modelling the impact of physical activity on public health: A review and critique," Health Policy, Elsevier, vol. 124(10), pages 1155-1164.
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    More about this item

    Keywords

    Effect decay; Mathematical modelling; Public health; Decision-making; Structural uncertainty;
    All these keywords.

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation

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