{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T12:53:16Z","timestamp":1776084796158,"version":"3.50.1"},"reference-count":33,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,7,14]],"date-time":"2023-07-14T00:00:00Z","timestamp":1689292800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002380","name":"Hanyang University","doi-asserted-by":"publisher","award":["HY-2020"],"award-info":[{"award-number":["HY-2020"]}],"id":[{"id":"10.13039\/501100002380","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:p>Artificial Intelligence (AI)-driven Digital Health (DH) systems are poised to play a critical role in the future of healthcare. In 2021, $57.2 billion was invested in DH systems around the world, recognizing the promise this concept holds for aiding in delivery and care management. DH systems traditionally include a blend of various technologies, AI, and physiological biomarkers and have shown a potential to provide support for individuals with various health conditions. Digital therapeutics (DTx) is a more specific set of technology-enabled interventions within the broader DH sphere intended to produce a measurable therapeutic effect. DTx tools can empower both patients and healthcare providers, informing the course of treatment through data-driven interventions while collecting data in real-time and potentially reducing the number of patient office visits needed. In particular, socially assistive robots (SARs), as a DTx tool, can be a beneficial asset to DH systems since data gathered from sensors onboard the robot can help identify in-home behaviors, activity patterns, and health status of patients remotely. Furthermore, linking the robotic sensor data to other DH system components, and enabling SAR to function as part of an Internet of Things (IoT) ecosystem, can create a broader picture of patient health outcomes. The main challenge with DTx, and DH systems in general, is that the sheer volume and limited oversight of different DH systems and DTxs is hindering validation efforts (from technical, clinical, system, and privacy standpoints) and consequently slowing widespread adoption of these treatment tools.<\/jats:p>","DOI":"10.3389\/fdgth.2023.1208350","type":"journal-article","created":{"date-parts":[[2023,7,15]],"date-time":"2023-07-15T06:21:30Z","timestamp":1689402090000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Conceptualizing socially-assistive robots as a digital therapeutic tool in healthcare"],"prefix":"10.3389","volume":"5","author":[{"given":"Cedomir","family":"Stanojevic","sequence":"first","affiliation":[]},{"given":"Casey C.","family":"Bennett","sequence":"additional","affiliation":[]},{"given":"Selma","family":"Sabanovic","sequence":"additional","affiliation":[]},{"given":"Sawyer","family":"Collins","sequence":"additional","affiliation":[]},{"given":"Kenna","family":"Baugus Henkel","sequence":"additional","affiliation":[]},{"given":"Zachary","family":"Henkel","sequence":"additional","affiliation":[]},{"given":"Jennifer A.","family":"Piatt","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2023,7,14]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1038\/s41746-019-0111-3","article-title":"Digital health: a path to validation","volume":"2","author":"Mathews","year":"2019","journal-title":"NPJ Digit Med"},{"key":"B2","year":""},{"key":"B3","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1038\/nbt.3495","article-title":"Digital medicine\u2019s march on chronic disease","volume":"34","author":"Kvedar","year":"2016","journal-title":"Nat Biotechnol"},{"key":"B4","doi-asserted-by":"publisher","first-page":"97","DOI":"10.30773\/pi.2019.01.20","article-title":"Could digital therapeutics be a game changer in psychiatry?","volume":"16","author":"Cho","year":"2019","journal-title":"Psychiatry Investig"},{"key":"B5","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1038\/s41746-022-00741-3","article-title":"Smartphone accelerometer data as a proxy for clinical data in modeling of bipolar disorder symptom trajectory","volume":"5","author":"Bennett","year":"","journal-title":"NPJ Digit Med"},{"key":"B6","author":"Goldsack","year":""},{"key":"B7","doi-asserted-by":"publisher","first-page":"106319","DOI":"10.1016\/j.cmpb.2021.106319","article-title":"Introduction of digital therapeutics","volume":"209","author":"Hong","year":"2021","journal-title":"Comput Methods Programs Biomed"},{"key":"B8","doi-asserted-by":"publisher","first-page":"6","DOI":"10.12793\/tcp.2019.27.1.6","article-title":"Digital therapeutics and clinical pharmacology","volume":"27","author":"Chung","year":"2019","journal-title":"Transl Clin Pharmacol"},{"key":"B9","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1038\/s41746-020-00370-8","article-title":"Characteristics and challenges of the clinical pipeline of digital therapeutics","volume":"3","author":"Patel","year":"2020","journal-title":"NPJ Digit Med"},{"key":"B10","year":"2023"},{"key":"B11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.31080\/asms.2020.04.0575","article-title":"Digital therapeutics-what they are, what they will be","volume":"4","author":"Recchia","year":"2020","journal-title":"Acta Sci Med Sci"},{"key":"B12","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1201\/9781420004137.ch1","article-title":"Excipients: background\/introduction","volume-title":"Excipient development for pharmaceutical, biotechnology, and drug delivery systems","author":"Bhattacharyya","year":"2006"},{"key":"B13","first-page":"536","author":"Bennett","year":"2017"},{"key":"B14","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1093\/jlb\/lsz013","article-title":"Integrating artificial intelligence into health care through data access: can the GDPR act as a beacon for policymakers?","volume":"6","author":"Forcier","year":"2019","journal-title":"J Law Biosci"},{"key":"B15","doi-asserted-by":"publisher","first-page":"EAAY7120","DOI":"10.1126\/scirobotics.aay7120","article-title":"XAI\u2014explainable artificial intelligence","volume":"4","author":"Gunning","year":"2019","journal-title":"Sci Robot"},{"key":"B16","first-page":"13","author":"Holzinger","year":"2022"},{"key":"B17","doi-asserted-by":"publisher","first-page":"110273","DOI":"10.1016\/j.knosys.2023.110273","article-title":"Explainable AI (XAI): a systematic meta-survey of current challenges and future opportunities","volume":"263","author":"Saeed","year":"2023","journal-title":"Knowl Based Syst"},{"key":"B18","article-title":"Privacy and Health Information. 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