{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T17:25:27Z","timestamp":1787851527096,"version":"build-2784847793"},"reference-count":48,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Mhealth Uhealth"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Cancer affects multiple physical, psychological, and social aspects of an individual\u2019s life. Cancer survivors frequently report unmet needs long after diagnosis and require ongoing support. AI is increasingly embedded in patient-facing digital health technologies (DHTs) in oncology, yet its impact on different domains of patients\u2019 and survivors\u2019 health-related quality of life (HRQOL) remains unclear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This systematic review aims to (1) examine how AI has been integrated into patient-facing DHTs designed to support cancer survivors, (2) narratively synthesize the potential effects of these technologies on HRQOL and provide preliminary quantitative estimates through an exploratory meta-analysis, and (3) explore broader changes in additional patient-reported outcomes (PROs; secondary aim).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>PubMed, PsycINFO, Embase, Scopus, CINAHL, and the Cochrane Library were searched for articles published between January 2020 and August 2025. Reference lists of included articles were hand-searched for additional eligible studies. Eligible studies enrolled cancer survivors of any age and disease stage, evaluated a patient-facing DHT with AI components, and assessed HRQOL. Nonoriginal research and non-English reports were excluded. Risk of bias was assessed in all controlled studies using RoB 2 (revised Cochrane risk of bias 2) or ROBINS-I V2 (Risk of Bias in Non-Randomized Studies\u2014of Interventions, Version 2), according to study design. Data on HRQOL and other PROs were synthesized narratively, and exploratory random-effects meta-analyses were conducted for HRQOL domains.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Eight reports from 7 studies from China and the United States (N=2867 participants) met the inclusion criteria, and 3 (n=292 participants) contributed to the exploratory meta-analysis. All studies included adults with various cancers at different stages and times since diagnosis. Most studies showed low risk of bias or some concerns (RoB 2), but one was evaluated as having a serious risk of bias (ROBINS-I V2). AI applications ranged from symptom monitoring to targeted education. The narrative synthesis suggested positive effects on selected HRQOL domains, particularly general health, with more pronounced effects in studies conducted in China. Exploratory meta-analyses demonstrated provisional moderate positive effects on global health (Hedges g=0.77, 95% CI 0.15\u20101.40) and social functioning (Hedges g=0.75, 95% CI 0.08\u20101.42), but no effects on physical functioning, role functioning, or emotional well-being. Other PROs indicated generally high user satisfaction and adherence, improved mental health outcomes, and reductions in physical symptoms. Only minor and mild adverse events were reported.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Current evidence, although limited, suggests that AI-enabled patient-facing DHTs may benefit survivors\u2019 HRQOL and other PROs, particularly in early survivorship. However, our findings are based on small and heterogeneous studies and should therefore be interpreted with caution. Robust trials with adequate sample sizes, longer follow-up, and appropriate control conditions, including DHTs without AI components, are needed to determine the specific contribution of AI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>PROSPERO CRD420251021466; https:\/\/www.crd.york.ac.uk\/PROSPERO\/view\/CRD420251021466<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/94793","type":"journal-article","created":{"date-parts":[[2026,8,10]],"date-time":"2026-08-10T20:11:52Z","timestamp":1786392712000},"page":"e94793","source":"Crossref","is-referenced-by-count":0,"title":["Patient-Facing AI-Enabled Digital Health Technologies and Quality of Life in Cancer: Systematic Review and Exploratory Meta-Analysis"],"prefix":"10.2196","volume":"14","author":[{"given":"Anica","family":"Ilic","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lene Kristine","family":"Juvet","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick","family":"Cairns","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kristen Elizabeth Thompson","family":"Thornton","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanne Cathrine","family":"Lie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,8,10]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1136\/gpsych-2022-100871"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s13187-020-01941-9"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/bjc.2016.352"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1177\/21501319221105248"},{"key":"ref5","unstructured":"Health AdvancesGuidance to industry: classification of digital health technologies20232026-06-04Digital Therapeutics Alliancehttps:\/\/dtxalliance.org\/wp-content\/uploads\/2023\/06\/Guidance-to-Industry-Classification-of-Digital-Health-Technologies-2023Jun05.pdf"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-024-01097-6"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-017-0012-2"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1177\/20552076251315621"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-323-90045-4.00006-X"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-818438-7.00012-5"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-323-90045-4.00013-7"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.pecinn.2023.100171"},{"key":"ref13","unstructured":"Definition of patient-reported outcome\u2014NCI dictionary of cancer termsNational Cancer Institute20112025-11-24https:\/\/www.cancer.gov\/publications\/dictionaries\/cancer-terms\/def\/patient-reported-outcome"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1177\/20406223211015958"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/B978-012373960-5.00336-1"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-1005-9_753"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-publhealth-052120-012811"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/S2589-7500(24)00047-5"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.n71"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-818438-7.00002-2"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.apjon.2022.100127"},{"key":"ref22","unstructured":"DefinitionsNational Cancer Institute\u2014Division of Cancer Control & Population Sciences2025-03-26https:\/\/cancercontrol.cancer.gov\/ocs\/definitions"},{"key":"ref23","unstructured":"Covidence2026-07-09https:\/\/www.covidence.org\/"},{"key":"ref24","unstructured":"SciSpace2026-07-09https:\/\/scispace.com\/"},{"key":"ref25","unstructured":"Perplexity AI2026-07-09https:\/\/www.perplexity.ai"},{"key":"ref26","author":"Higgins, JPT","year":"2024","journal-title":"Cochrane Handbook for Systematic Reviews of Interventions Version 65"},{"key":"ref27","unstructured":"ROBINS-i V2Risk of Bias Tools20252026-07-09https:\/\/www.riskofbias.info\/welcome\/robins-i-v2"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.l6890"},{"key":"ref29","unstructured":"Stata Statistical Software: Release 19StataCorp20252026-07-15https:\/\/www.stata.com\/new-in-stata\/"},{"issue":"6","key":"ref30","first-page":"654","volume":"58","author":"Jiang, L","year":"2023","journal-title":"Chin J Nurs"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3779\/j.issn.1009-3419.2025.102.11"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1200\/CCI.24.00085"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare10112261"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-025-01439-y"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.2196\/50783"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpainsymman.2024.05.033"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.2196\/60115"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s00520-023-07884-3"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-92762-7"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.2196\/49089"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.critrevonc.2020.103123"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/S2589-7500(21)00132-1"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1007\/s10551-005-5353-0"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s00520-024-08866-9"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.3389\/fdgth.2025.1536416"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1177\/21565333251377393"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0000651"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pdig.0001235"}],"container-title":["JMIR mHealth and uHealth"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/mhealth.jmir.org\/2026\/1\/e94793","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T16:49:59Z","timestamp":1787849399000},"score":1,"resource":{"primary":{"URL":"https:\/\/mhealth.jmir.org\/2026\/1\/e94793"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,10]]},"references-count":48,"URL":"https:\/\/doi.org\/10.2196\/94793","relation":{},"ISSN":["2291-5222"],"issn-type":[{"value":"2291-5222","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,10]]}}}