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Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Chronic pain (CP) is a debilitating condition that extends beyond persistent pain, influenced by physiological and psychological factors. However, clinical trials often evaluate outcomes solely on self-reported pain amplitude. To address this, we aimed to derive a single metric from multidimensional digital data to comprehensively represent wellness in lower back and leg pain. Daily-reported data were collected for five years (&gt;190\u2009K samples,\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u2009498, from NCT01719055\/NCT03240588), comprised of clinical assessments, digitally-reported symptoms, text responses, and smartwatch-based actigraphy. Clustering analysis of the digital data identified five novel symptom clusters. They were validated by comparing centroid distances to standard assessments, revealing five ordinal best-to-worst states (r\u2009=\u20090.34 to r\u2009=\u2009\u22120.51, ps\u2009&lt;\u20090.001), even when pain magnitude was similar. Further, patients\u2019 text messages about their status associated better with the clusters than pain reports alone. This solution extends beyond a recapitulation of pain level, yielding non-obvious, meaningful states that serve as an actionable metric in CP care.\n                  <\/jats:p>","DOI":"10.1038\/s41746-025-02084-1","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T13:15:04Z","timestamp":1763730904000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Defining and validating a multidimensional digital metric of health states in chronic back and leg pain"],"prefix":"10.1038","volume":"8","author":[{"given":"Jenna M.","family":"Reinen","sequence":"first","affiliation":[]},{"given":"Carla","family":"Agurto","sequence":"additional","affiliation":[]},{"given":"Guillermo","family":"Cecchi","sequence":"additional","affiliation":[]},{"name":"NAVITAS and ENVISION Studies Physician Author Group","sequence":"additional","affiliation":[]},{"given":"Richard","family":"Rauck","sequence":"additional","affiliation":[]},{"given":"Eric","family":"Loudermilk","sequence":"additional","affiliation":[]},{"given":"Julio","family":"Paez","sequence":"additional","affiliation":[]},{"given":"Louis","family":"Bojrab","sequence":"additional","affiliation":[]},{"given":"John","family":"Noles","sequence":"additional","affiliation":[]},{"given":"Todd","family":"Turley","sequence":"additional","affiliation":[]},{"given":"Mohab","family":"Ibrahim","sequence":"additional","affiliation":[]},{"given":"Amol","family":"Patwardhan","sequence":"additional","affiliation":[]},{"given":"James","family":"Scowcroft","sequence":"additional","affiliation":[]},{"given":"Rene","family":"Przkora","sequence":"additional","affiliation":[]},{"given":"Nathan","family":"Miller","sequence":"additional","affiliation":[]},{"given":"Gassan","family":"Chaiban","sequence":"additional","affiliation":[]},{"name":"Boston Scientific Research Scientists Consortium","sequence":"additional","affiliation":[]},{"given":"Dat","family":"Huynh","sequence":"additional","affiliation":[]},{"given":"Kristen","family":"Lechleiter","sequence":"additional","affiliation":[]},{"given":"Brad","family":"Hershey","sequence":"additional","affiliation":[]},{"given":"Rex","family":"Woon","sequence":"additional","affiliation":[]},{"given":"Matt","family":"McDonald","sequence":"additional","affiliation":[]},{"given":"Jeffrey L.","family":"Rogers","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"2084_CR1","doi-asserted-by":"publisher","first-page":"e328","DOI":"10.1097\/j.pain.0000000000002291","volume":"163","author":"RJ Yong","year":"2022","unstructured":"Yong, R. 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The Boston Scientific Research Scientists Consortium are or were full-time, salaried employees of Boston Scientific. Jenna Reinen, Carla Agurto, Guillermo Cecchi, and Jeffrey L. Rogers are full-time, salaried employees of IBM Research. The IBM team has filed and holds patents related to free-text analysis (GC, US9508360B2), health states (filed, JMR, CA, GC, JLR, P202304058US01), state prediction (GC, US8799202B2), and adaptive pain management (JLR, CA3099523A1).","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"713"}}