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dc.contributor.authorShavazipour, Babooshka
dc.contributor.authorAfsar, Bekir
dc.contributor.authorMultanen, Juhani
dc.contributor.authorMiettinen, Kaisa
dc.contributor.authorKujala, Urho M.
dc.date.accessioned2022-01-18T09:59:40Z
dc.date.available2022-01-18T09:59:40Z
dc.date.issued2022
dc.identifier.citationShavazipour, 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. <i>Annals of Medicine</i>, <i>54</i>(1), 181-194. <a href="https://doi.org/10.1080/07853890.2021.2024876" target="_blank">https://doi.org/10.1080/07853890.2021.2024876</a>
dc.identifier.otherCONVID_103864678
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/79391
dc.description.abstractBackground: There are no explicit guidelines or tools available to support clinicians in selecting exercise therapy modalities according to the characteristics of individual patients despite the apparent need. 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.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherTaylor & Francis
dc.relation.ispartofseriesAnnals of Medicine
dc.rightsCC BY 4.0
dc.subject.otherknee osteoarthritis
dc.subject.othercost-effective exercise therapy modality
dc.subject.otherpain
dc.subject.otherphysical function
dc.subject.otherdecision making
dc.subject.otherdecision support
dc.titleInteractive multiobjective optimization for finding the most preferred exercise therapy modality in knee osteoarthritis
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202201181160
dc.contributor.laitosLiikuntatieteellinen tiedekuntafi
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Sport and Health Sciencesen
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineFysioterapiafi
dc.contributor.oppiaineLaskennallinen tiedefi
dc.contributor.oppiaineLiikuntalääketiedefi
dc.contributor.oppiaineMultiobjective Optimization Groupfi
dc.contributor.oppiainePäätöksen teko monitavoitteisestifi
dc.contributor.oppiainePhysiotherapyen
dc.contributor.oppiaineComputational Scienceen
dc.contributor.oppiaineSports and Exercise Medicineen
dc.contributor.oppiaineMultiobjective Optimization Groupen
dc.contributor.oppiaineDecision analytics utilizing causal models and multiobjective optimizationen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange181-194
dc.relation.issn0785-3890
dc.relation.numberinseries1
dc.relation.volume54
dc.type.versionpublishedVersion
dc.rights.copyright© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber322221
dc.subject.ysokipu
dc.subject.ysopolvet
dc.subject.ysopäätöksentukijärjestelmät
dc.subject.ysofyysinen toimintakyky
dc.subject.ysooptimointi
dc.subject.ysofysioterapia
dc.subject.ysoliikuntahoito
dc.subject.ysonivelrikko
dc.subject.ysomonitavoiteoptimointi
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p14193
jyx.subject.urihttp://www.yso.fi/onto/yso/p14204
jyx.subject.urihttp://www.yso.fi/onto/yso/p27803
jyx.subject.urihttp://www.yso.fi/onto/yso/p27172
jyx.subject.urihttp://www.yso.fi/onto/yso/p13477
jyx.subject.urihttp://www.yso.fi/onto/yso/p10515
jyx.subject.urihttp://www.yso.fi/onto/yso/p7811
jyx.subject.urihttp://www.yso.fi/onto/yso/p12334
jyx.subject.urihttp://www.yso.fi/onto/yso/p32016
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1080/07853890.2021.2024876
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundinginformationThis research was partly funded by the Academy of Finland [grant no. 322221].
dc.type.okmA1


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