Computational Mechanisms of Attribute Translations

Computational Mechanisms of Attribute Translations | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Computational Mechanisms of Attribute Translations Barbara Oberbauer, Ulf Hahnel, Sebastian Gluth This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7471672/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract Attribute translations, a choice architecture intervention technique aiming to promote behavior change by translating decision-relevant information into more comprehensible and meaningful units for laypersons (e.g., translating nutritional information into a rating scale), have been extensively adopted by policymakers in recent years. However, little is known about the computational mechanisms that underlie their effects on behavior. To address this gap, we investigate the role of visual attention in inducing behavior change by modeling the dynamic interplay of information acquisition and evidence accumulation. For our analyses, we used a pre-existing data set from an online process tracing study in which participants completed a multi-attribute value-based decision-making task. Participants performed the task twice, with and without an additional translation of the items' energy and water consumption. Our modeling results suggest that behaviorally less effective attribute translations (in the form of numeric information) only affected participants' response caution. In contrast, behaviorally effective attribute translations (in the form of a qualitative rating) impacted participants' preference formation by shifting the attribute weights in favor of the translated attribute as well as by decreasing the bias on the attended option. These findings add critical insights to the ongoing debate on the degree of agency that is promoted by choice architecture interventions as they imply that attribute translations may promote more considerate, preference-aligned decisions rather than simply provide pre-decisional shortcuts. Social science/Psychology/Human behaviour Scientific community and society/Social sciences/Decision making Full Text Additional Declarations There is NO Competing Interest. This study utilized data from a previously published source, Mertens et al., 2020. The corresponding author of that prior publication confirmed that both studies were approved by the University Commission for Ethical Research in Geneva (CUREG2.0). Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7471672","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":510269412,"identity":"cc40fc5e-d4dc-4aae-870e-d84dde68f9b4","order_by":0,"name":"Barbara Oberbauer","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0002-8993-0775","institution":"University of Hamburg","correspondingAuthor":true,"prefix":"","firstName":"Barbara","middleName":"","lastName":"Oberbauer","suffix":""},{"id":510269413,"identity":"963055a7-1481-4231-8c8f-353642d06e20","order_by":1,"name":"Ulf Hahnel","email":"","orcid":"https://orcid.org/0000-0002-0595-5899","institution":"Leuphana University Lüneburg","correspondingAuthor":false,"prefix":"","firstName":"Ulf","middleName":"","lastName":"Hahnel","suffix":""},{"id":510269414,"identity":"a459228d-67a1-46aa-b158-62c45b557929","order_by":2,"name":"Sebastian Gluth","email":"","orcid":"https://orcid.org/0000-0003-2241-5103","institution":"Universität Hamburg","correspondingAuthor":false,"prefix":"","firstName":"Sebastian","middleName":"","lastName":"Gluth","suffix":""}],"badges":[],"createdAt":"2025-08-27 12:37:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7471672/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7471672/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90686293,"identity":"8c547182-ac68-4b98-941a-7d430ce47190","added_by":"auto","created_at":"2025-09-05 16:58:25","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7068267,"visible":true,"origin":"","legend":"Article File","description":"","filename":"computationalmechanismsofattributetranslations.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7471672/v1_covered_98bece38-3a30-4298-afab-17b421c85c2f.pdf"}],"financialInterests":"\u003cp\u003eThere is \u003cstrong\u003eNO\u003c/strong\u003e Competing Interest.\u003c/p\u003e\n\u003cp\u003eThis study utilized data from a previously published source, Mertens et al., 2020. 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