{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T05:43:13Z","timestamp":1783921393476,"version":"3.55.0"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T00:00:00Z","timestamp":1755820800000},"content-version":"vor","delay-in-days":50,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000056","name":"National Institute of Nursing Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000056","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01NR019639"],"award-info":[{"award-number":["R01NR019639"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,7,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Studies on symptom concordance between patients and their caregivers often use cross-sectional designs, which may fail to capture the longitudinal, dynamic symptom experience. The Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C) is a remote health monitoring system that utilizes smartwatches and ecological momentary assessments (EMAs) to empower patients and caregivers to monitor and manage cancer pain at home. BESI-C collects real-time symptom data in naturalistic settings, enabling longitudinal tracking and analysis of symptom patterns over time.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>To define and examine dyadic concordance using participant-initiated symptom reports collected via remote health monitoring.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>Dyads of patients with advanced cancer and their family caregivers were recruited to use BESI-C for 2 weeks, reporting pain in real time through EMAs. We used Bangdiwala\u2019s B statistic to determine the concordance of patient-reported pain and caregiver-reported perceived patient pain under different contextual criteria (eg, co-location of participants; user engagement with BESI-C) that we hypothesized would impact concordance. We also explored a hypothesis that concordance would improve between study week 1 versus week 2.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Data from 21 patient-caregiver dyads were used for analysis. The reporting of pain events was highly variable between patients and their caregivers. Concordance of pain reporting improved when patients and caregivers were co-located and both wearing their BESI-C smartwatches. We did not observe consistent patterns in patient-caregiver concordance between week 1 and week 2.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>We propose an analytical approach to define and evaluate concordance between patients\u2019 and caregivers\u2019 real-time symptom reports that can be applied to dyadic, longitudinal symptom data collected using remote health monitoring. Future work should examine the relationship between patient-caregiver symptom concordance with key quality-of-life metrics and sociodemographic factors that impact participant engagement with remote health monitoring technologies.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamiaopen\/ooaf088","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T18:41:53Z","timestamp":1755888113000},"source":"Crossref","is-referenced-by-count":3,"title":["Defining dyadic cancer pain concordance using participant-initiated interactions with a remote health monitoring system"],"prefix":"10.1093","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5239-4046","authenticated-orcid":false,"given":"Mina","family":"Ostovari","sequence":"first","affiliation":[{"name":"School of Nursing, University of Virginia (UVA) , Charlottesville, VA 22903,","place":["United 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