[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-82376-en":3,"doc-seo-82376-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},82376,1099514068365,"Aurelia","https://ap-avatar.wpscdn.com/avatar/10000253d8d9f28188e?_k=1776742907772140068",8,"Research & Report","Learning When to Intervene on Habitual Behaviors: A Case Study in Oral Health Care","Digital health interventions face a key challenge: choosing when to deliver prompts for habitual behaviors like tooth brushing or eating. Fixed intervention timing can drift out of sync as routines change, arriving too early or after the behavior, which reduces usefulness. The work proposes an online decision-making framework that continuously adapts intervention timing from evolving individual behavior patterns, embedding timing selection in a sequential process that decides both when and whether to intervene. Evaluations on an oral health trial show improved coverage versus fixed schedules, with preliminary results consistent with prior findings.","arXiv :2607 .09518v1 [ cs .HC] 10 Jul 2026  \nLearning When to Intervene on Habitual Behaviors: A Case Study in Oral Health Care  \nBHANU TEJA GULLAPALLI, Harvard University, USAVIVEK SHETTY, University of California, Los Angeles, USA  \nANNA L. TRELLA, Harvard University, USA ASIM H. GAZI, Harvard University, USA SUSAN A. MURPHY∗ , Harvard University, USA  \nA central challenge for digital health interventions aimed at improving habitual behaviors is deciding when to deliver an intervention prompt. For many daily habits—such as tooth brushing or eating—individuals tend to act around a usual time of day, but this timing isnot fixed and can shift as routines evolve. When intervention timing is selected in advance and held constant throughout a study, it can gradually become misaligned with behavior, causing interventions to potentially arrive after the behavior has already occurred or too early to be effective. In this work, we address this habitual timing misalignment in digital health interventions by proposing an online decision-making framework that continuously adapts intervention timing as individual behavior patterns change. Rather than treating intervention timing as a static design choice, our framework adapts it over time and integrates it into a sequential process that determines both when and whether to deliver an intervention. Using data from a deployed oral health intervention trial as a case study, we evaluate our approach using both observed data and simulated settings to assess how well different intervention timing strategies align with the timing of brushing events. Across these evaluations, we measure performance using a coverage-based metric that captures whether an intervention is delivered sufficiently close to a subsequent brushing event. We find that adaptive intervention timing consistently improves coverage compared to fixed intervention times based on user-provided input. The proposed framework is currently deployed in an ongoing randomized controlled trial of a digital oral health intervention, with preliminary results that are consistent with and further support our prior evaluations.  \nCCS Concepts: • Human-centered computing → Ubiquitous and mobile computing; • Applied computing → Health informatics;  \n• Computing methodologies → Online learning settings.  \nAdditional Key Words and Phrases: digital health interventions, adaptive intervention timing, online learning, just-in-time adaptive interventions, oral health, habitual behavior  \n1 Introduction  \nDigital health interventions aim to support health-related behaviors by delivering timely and relevant prompts in individual’s everyday lives. In recent years, the widespread adoption of smartphones, wearable devices, and connected health technologies has enabled the continuous collection of fine-grained behavioral and contextual data outside of clinical settings. These technologies have made it increasingly feasible to monitor daily activities such as physical activity, eating, sleep, or oral self-care in real time, and to deliver interventions directly through personal devices as individuals go about their routines [5, 14, 18, 23] .  \n∗ Susan A. Murphy holds concurrent appointments at Harvard University and as an Amazon Scholar. This paper describes work performed at Harvard University and is not associated with Amazon.  \nAuthors’ Contact Information: Bhanu Teja Gullapalli, [bgullapalli@g.harvard.edu](bgullapalli@g.harvard.edu), Department of Statistics and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA; Vivek Shetty, [vshetty@g.ucla.edu](vshetty@g.ucla.edu), School of Dentistry, University of California, Los Angeles, Los Angeles, California, USA; Anna L. Trella, [atrella@g.harvard.edu](atrella@g.harvard.edu), Department of Statistics and School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA; Asim H. Gazi, [agazi@seas.harvard.edu](agazi@seas.harvard.edu), Department","cbCaikTmhjbS5WQi","https://ap.wps.com/l/cbCaikTmhjbS5WQi","pdf",998214,2,1,27,"English","en",105,"# Introduction\n## Digital health interventions and timely prompts\n## Habitual behaviors and timing misalignment\n# Adaptive online decision-making framework\n## Continuous adaptation of intervention timing\n## Sequential decision process for delivery","[{\"question\":\"Why is intervention timing difficult for habitual behaviors in digital health?\",\"answer\":\"Because habits occur around a usual time of day but shift as routines evolve, so prompts scheduled in advance can become misaligned with when the behavior actually happens.\"},{\"question\":\"What problem does the proposed work address?\",\"answer\":\"Habitual timing misalignment, where intervention prompts arrive too early or after the target behavior due to fixed timing design choices.\"},{\"question\":\"How does the proposed framework evaluate performance and what does it find?\",\"answer\":\"It uses observed trial data and simulated settings, measuring performance with a coverage-based metric that checks whether prompts are delivered close to subsequent brushing events; adaptive timing improves coverage compared with fixed intervention times.\"}]",1784180013,68,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"learning-when-to-intervene-on-habitual-behaviors-a-case-study-in-oral-health-care","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,47,50],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":20},"https://docshare.wps.com/document/","Document",{"item":48,"name":12,"@type":43,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/learning-when-to-intervene-on-habitual-behaviors-a-case-study-in-oral-health-care/82376/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-23","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is intervention timing difficult for habitual behaviors in digital health?","Question",{"text":75,"@type":76},"Because habits occur around a usual time of day but shift as routines evolve, so prompts scheduled in advance can become misaligned with when the behavior actually happens.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What problem does the proposed work address?",{"text":80,"@type":76},"Habitual timing misalignment, where intervention prompts arrive too early or after the target behavior due to fixed timing design choices.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the proposed framework evaluate performance and what does it find?",{"text":84,"@type":76},"It uses observed trial data and simulated settings, measuring performance with a coverage-based metric that checks whether prompts are delivered close to subsequent brushing events; adaptive timing improves coverage compared with fixed intervention times.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]