A1 Journal article (refereed)
Interactive multiobjective optimization for finding the most preferred exercise therapy modality in knee osteoarthritis (2022)
Shavazipour, B., Afsar, B., Multanen, J., Miettinen, K., & Kujala, U. M. (2022). Interactive multiobjective optimization for finding the most preferred exercise therapy modality in knee osteoarthritis. Annals of Medicine, 54(1), 181-194. https://doi.org/10.1080/07853890.2021.2024876
JYU authors or editors
Publication details
All authors or editors: Shavazipour, Babooshka; Afsar, Bekir; Multanen, Juhani; Miettinen, Kaisa; Kujala, Urho M.
Journal or series: Annals of Medicine
ISSN: 0785-3890
eISSN: 1365-2060
Publication year: 2022
Publication date: 13/01/2022
Volume: 54
Issue number: 1
Pages range: 181-194
Publisher: Taylor & Francis
Publication country: United Kingdom
Publication language: English
DOI: https://doi.org/10.1080/07853890.2021.2024876
Publication open access: Openly available
Publication channel open access: Open Access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/79391
Web address of parallel published publication (pre-print): https://www.researchsquare.com/article/rs-77399/v1
Abstract
Objective: This study develops a methodology based on a novel multiobjective optimization model and examines its feasibility as a decision support tool to support healthcare professionals in comparing different modalities and identifying the most preferred one based on a patient’s needs.
Methods: Thirty-one exercise therapy modalities were considered from 21 randomized controlled trials. A novel interactive multiobjective optimization model was designed to characterize the efficacy of an exercise therapy modality based on five objectives: minimizing cost, maximizing pain reduction, maximizing disability improvement, minimizing the number of supervised sessions, and minimizing the length of the treatment period. An interactive model incorporates clinicians’ preferences in finding the most preferred exercise therapy modality for each need. Multiobjective optimization methods are mathematical algorithms designed to identify the optimal balance between multiple conflicting objectives among available solutions/alternatives. They explicitly evaluate the conflicting objectives and support decision-makers in identifying the best balance. An experienced research-oriented physiotherapist was involved as a decisionmaker in the interactive solution process testing the proposed decision support tool.
Results: The proposed methodology design and interactive process of the tool, including preference information, graphs, and exercise suggestions following the preferences, can help clinicians to find the most preferred exercise therapy modality based on a patient’s needs and health status; paving the way to individualize recommendations.
Conclusions: We examined the feasibility of our decision support tool using an interactive multiobjective optimization method designed to help clinicians balance between conflicting objectives to find the most preferred exercise therapy modality for patients with knee osteoarthritis. The proposed methodology is generic enough to be applied in any field of medical and healthcare settings, where several alternative treatment options exist.
Keywords: knees; arthrosis; pain; physical functioning; physiotherapy; exercise therapy; optimisation; decision support systems; multi-objective optimisation
Free keywords: knee osteoarthritis; cost-effective exercise therapy modality; pain; physical function; decision making; decision support
Contributing organizations
Related projects
- Data-driven Decision Support with Multiobjective Optimization (DAEMON)
- Miettinen, Kaisa
- Research Council of Finland
Ministry reporting: Yes
VIRTA submission year: 2022
JUFO rating: 2
- Computational Science (Faculty of Information Technology IT) LASK
- Multiobjective Optimization Group (Faculty of Information Technology IT) MOG
- Physiotherapy (Faculty of Sport and Health Sciences LTK, SPORT) FTE
- Sports and Exercise Medicine (Faculty of Sport and Health Sciences LTK, SPORT) LLT
- Decision analytics utilizing causal models and multiobjective optimization (University of Jyväskylä JYU) DEMO; 2017-2021