{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,30]],"date-time":"2026-10-30T01:39:33Z","timestamp":1793324373835,"version":"4.5.0"},"reference-count":26,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T00:00:00Z","timestamp":1661731200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Israel Innovation Authority","award":["67388"],"award-info":[{"award-number":["67388"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Objectives<\/jats:title>\n<jats:p>Despite documented benefits and physicians\u2019 recommendations to participate in cardiac rehabilitation (CR) programs, the average dropout rate remains between 12\u201356%. This study\u2019s goal was to demonstrate that using personalized interventions can significantly increase patient adherence.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Method<\/jats:title>\n<jats:p>Ninety-five patients (ages 18\u201390) eligible for the CR program were randomly recruited and received personalized interventions using the Well-Beat system. Adherence levels were compared to those of a historical control group. The Well-Beat system provided Sheba CR Health Care Provider (HCP) guidelines for personalized patient-therapist dialogue. The system also generated ongoing personalized text messages for each patient sent twice a week and related each patient\u2019s dynamic profile to their daily behavior, creating continuity, and reinforcing the desired behavior.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>A significant increase in patient adherence to the CR program: Three months after initiation, 76% remained active compared to the historical average of 24% in the matched control group (log-rank p-value = 0.001).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusions<\/jats:title>\n<jats:p>Using an Artificial Intelligence (AI)-based engine that generated recommendations and messages made it possible to improve patient adherence without increasing HCP load, benefiting all. Presenting customized patient insights to the HCP and generating personalized communications along with action motivating text messages can also be useful for remote care.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0273815","type":"journal-article","created":{"date-parts":[[2022,8,29]],"date-time":"2022-08-29T17:40:50Z","timestamp":1661794850000},"page":"e0273815","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":33,"title":["Improving cardiac rehabilitation patient adherence via personalized interventions"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8845-823X","authenticated-orcid":true,"given":"Keren B.","family":"Aharon","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5111-5252","authenticated-orcid":true,"given":"Avital","family":"Gershfeld-Litvin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0364-8027","authenticated-orcid":true,"given":"On","family":"Amir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Irene","family":"Nabutovsky","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Klempfner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2022,8,29]]},"reference":[{"issue":"9","key":"pone.0273815.ref001","doi-asserted-by":"crossref","first-page":"e104","DOI":"10.1161\/CIR.0000000000000756","article-title":"Recommendations for Cardiovascular Health and Disease Surveillance for 2030 and Beyond: A Policy Statement from the American Heart Association","volume":"141","author":"VL Roger","year":"2020","journal-title":"Circulation"},{"issue":"2","key":"pone.0273815.ref002","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1177\/2047487316680692","article-title":"Cardiac rehabilitation following an acute coronary syndrome: Trends in referral, predictors and mortality outcome in a multicenter national registry between years 2006\u20132013: Report from the Working Group on Cardiac Rehabilitation, the Israeli Heart Society","volume":"24","author":"F Chernomordik","year":"2017","journal-title":"European Journal of Preventive Cardiology"},{"key":"pone.0273815.ref003","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.eclinm.2019.06.006","article-title":"Nature of cardiac rehabilitation around the globe","volume":"13","author":"M Supervia","year":"2019","journal-title":"EClinicalMedicine"},{"key":"pone.0273815.ref004","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.eclinm.2019.06.007","article-title":"Cardiac rehabilitation availability and density around the globe","volume":"13","author":"K Turk-Adawi","year":"2019","journal-title":"EClinicalMedicine"},{"issue":"2","key":"pone.0273815.ref005","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.mayocp.2016.10.014","article-title":"Increasing cardiac rehabilitation participation from 20% to 70%: a road map from the Million Hearts Cardiac Rehabilitation Collaborative","volume":"92","author":"PA Ades","year":"2017","journal-title":"Mayo Clinic Proceedings"},{"issue":"2","key":"pone.0273815.ref006","first-page":"206","article-title":"Adherence to a cardiac rehabilitation home program model of care: a comparison to a well-established traditional on-site supervised program. 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