The Weight of the Past: History-Dependent Resistance in Effort Disengagement

preprint OA: closed
Full text JSON View at publisher
AI-generated deep summary by claude@2026-07, 2026-07-05 · read from full text

The paper studied how effort-related disengagement develops over time and whether modeling resistance as history-dependent (rather than memoryless) improves prediction. Using a publicly available motor-activity time series dataset from people diagnosed with major depressive disorder, schizophrenia, and ADHD, the authors compared baseline memoryless behavioural models with history-sensitive alternatives that include prior resistance escalation. Across diagnostic groups, models augmented with short-term temporal features improved predictive accuracy and showed consistent hysteresis effects, where disengagement likelihood depended on both current state and prior resistance trajectories. The work is explicitly a preprint and not peer reviewed, and the abstract does not describe additional limitations beyond this. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

Abstract Effort-related disengagement in psychiatric populations often unfolds gradually, even in the absence of overt motivational decline or changes in external task demands. Conventional behavioural models typically treat resistance as a memoryless function of momentary state variables. In this study, we investigate whether incorporating recent behavioural history improves the modelling of effort disengagement. Using a publicly available time series dataset of motor activity collected from individuals diagnosed with major depressive disorder, schizophrenia, and attention-deficit/hyperactivity disorder (ADHD), we compare baseline memoryless models with history-sensitive alternatives that incorporate prior resistance escalation. Across diagnostic groups, models augmented with short-term temporal features yielded superior predictive accuracy and revealed consistent hysteresis effects, whereby the likelihood of disengagement was modulated not only by current state conditions but also by prior trajectories of resistance. These findings suggest that resistance dynamics may exhibit temporal dependencies and asymmetries, highlighting the need for models of cognitive availability that incorporate recent behavioural context without requiring fundamental revisions to existing theoretical frameworks.
Full text 10,210 characters · extracted from preprint-html · click to expand
The Weight of the Past: History-Dependent Resistance in Effort Disengagement | 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 Research Article The Weight of the Past: History-Dependent Resistance in Effort Disengagement Nikesh Lagun This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8376762/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Effort-related disengagement in psychiatric populations often unfolds gradually, even in the absence of overt motivational decline or changes in external task demands. Conventional behavioural models typically treat resistance as a memoryless function of momentary state variables. In this study, we investigate whether incorporating recent behavioural history improves the modelling of effort disengagement. Using a publicly available time series dataset of motor activity collected from individuals diagnosed with major depressive disorder, schizophrenia, and attention-deficit/hyperactivity disorder (ADHD), we compare baseline memoryless models with history-sensitive alternatives that incorporate prior resistance escalation. Across diagnostic groups, models augmented with short-term temporal features yielded superior predictive accuracy and revealed consistent hysteresis effects, whereby the likelihood of disengagement was modulated not only by current state conditions but also by prior trajectories of resistance. These findings suggest that resistance dynamics may exhibit temporal dependencies and asymmetries, highlighting the need for models of cognitive availability that incorporate recent behavioural context without requiring fundamental revisions to existing theoretical frameworks. Psychiatry Psychology Cognitive Resistance Temporal Dynamics Lagun’s Law Effort Disengagement Psychiatric Behavior Motor Activity Time Series Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted 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-8376762","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":561210066,"identity":"73d6448a-3dab-467a-a1a7-5623c320956a","order_by":0,"name":"Nikesh Lagun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIiWNgGAWjYBACPgglYcDAwMP4IKGCTQ7EPfAAjxY2JC3MBh/O8BmDtSQQ1sIA0sImObNFLrEBxMWrhf34NenCHRbG/PxnD0jzNpilzw87/BBoi52cbgMOLTw5ZdIzz0iYSc7ISzDm3ZGWu/F2mgFQS7Kx2QFcDstJk+Ztk7AxuMFjkMx75ljuxtkJIC0HErfh0sL/BqLF/vwZg8O8bf/TDWenf8CvRSL9GEiLmQFDjmHjzDa2BHnpHAK2SLxhtgZqMZa4kWPM8OEMm+EG6ZyCAwkGuP3Cz5/+8DZvW51hf/8Z8x/AqJSXn52++cOHCjs5XFqA0WGAyjcAqzTAohIO2B+g8uUb8KkeBaNgFIyCkQgA2p5cQBVdBDgAAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0005-6372-4852","institution":"Independent Researcher","correspondingAuthor":true,"prefix":"","firstName":"Nikesh","middleName":"","lastName":"Lagun","suffix":""}],"badges":[],"createdAt":"2025-12-16 13:38:52","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8376762/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8376762/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98441025,"identity":"675da27c-bce4-41c7-ba59-2f564c538f0d","added_by":"auto","created_at":"2025-12-17 17:04:46","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":548155,"visible":true,"origin":"","legend":"","description":"","filename":"TheWeightofthePastHistoryDependentResistanceinEffortDisengagement.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8376762/v1_covered_fd48062a-89e2-4a18-aa79-6b97fc0f348d.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe Weight of the Past: History-Dependent Resistance in Effort Disengagement\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cognitive Resistance, Temporal Dynamics, Lagun’s Law, Effort Disengagement, Psychiatric Behavior, Motor Activity Time Series","lastPublishedDoi":"10.21203/rs.3.rs-8376762/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8376762/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEffort-related disengagement in psychiatric populations often unfolds gradually, even in the absence of overt motivational decline or changes in external task demands. Conventional behavioural models typically treat resistance as a memoryless function of momentary state variables. In this study, we investigate whether incorporating recent behavioural history improves the modelling of effort disengagement. Using a publicly available time series dataset of motor activity collected from individuals diagnosed with major depressive disorder, schizophrenia, and attention-deficit/hyperactivity disorder (ADHD), we compare baseline memoryless models with history-sensitive alternatives that incorporate prior resistance escalation. Across diagnostic groups, models augmented with short-term temporal features yielded superior predictive accuracy and revealed consistent hysteresis effects, whereby the likelihood of disengagement was modulated not only by current state conditions but also by prior trajectories of resistance. These findings suggest that resistance dynamics may exhibit temporal dependencies and asymmetries, highlighting the need for models of cognitive availability that incorporate recent behavioural context without requiring fundamental revisions to existing theoretical frameworks.\u003c/p\u003e","manuscriptTitle":"The Weight of the Past: History-Dependent Resistance in Effort Disengagement","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-17 07:22:25","doi":"10.21203/rs.3.rs-8376762/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"310a3f9c-f6cb-4797-8872-c378427048bd","owner":[],"postedDate":"December 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59752191,"name":"Psychiatry"},{"id":59752192,"name":"Psychology"}],"tags":[],"updatedAt":"2025-12-17T07:22:25+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-17 07:22:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8376762","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8376762","identity":"rs-8376762","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: preprint-html

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2025) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00