{"doi":"10.1161/jaha.123.032126","title":"Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System","abstract":"<jats:sec sec-type=\"background\" xml:lang=\"en\">\n            <jats:title>Background</jats:title>\n            <jats:p xml:lang=\"en\">Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking.</jats:p>\n          </jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results</jats:title>\n            <jats:p xml:lang=\"en\">WATCH‐IT (Wearable Activity Tracking for Comprehensive Healthcare‐Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20‐question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device‐related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10‐year increase [95% CI, 0.77–0.82]), male sex (OR, 0.87 [95% CI, 0.80–0.95]), and heart failure (OR, 0.75 [95% CI, 0.63–0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1‐quartile increase [95% CI, 1.04–1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05–1.30]) were associated with greater odds of device use.</jats:p>\n          </jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions</jats:title>\n            <jats:p xml:lang=\"en\">Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.</jats:p>\n          </jats:sec>","journal":"Journal of the American Heart Association","year":2024,"id":652594,"datarank":0.44166584687496613,"base_score":2.9444389791664403,"endowment":2.9444389791664403,"self_citation_contribution":0.44166584687496613,"citation_network_contribution":0.0,"self_endowment_contribution":0.44166584687496613,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":18,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":552483,"name":"Shaan Khurshid","orcid":"0000-0002-2840-4539","position":1,"is_corresponding":false},{"id":1702416,"name":"Mia Grayson","orcid":null,"position":2,"is_corresponding":false},{"id":798140,"name":"Jeffrey M. Ashburner","orcid":"0000-0002-5600-3492","position":3,"is_corresponding":false},{"id":639947,"name":"Mostafa A. Al‐Alusi","orcid":"0000-0002-9359-1641","position":4,"is_corresponding":false},{"id":385230,"name":"Yuchiao Chang","orcid":"0000-0003-1093-3755","position":5,"is_corresponding":false},{"id":263591,"name":"Andrea S. Foulkes","orcid":"0000-0002-9520-0501","position":6,"is_corresponding":false},{"id":896,"name":"Patrick T. Ellinor","orcid":"0000-0002-2067-0533","position":7,"is_corresponding":false},{"id":306787,"name":"David D. McManus","orcid":"0000-0002-9343-6203","position":8,"is_corresponding":false},{"id":337846,"name":"Daniel E. Singer","orcid":"0000-0001-6145-4848","position":9,"is_corresponding":false},{"id":583493,"name":"Steven J. Atlas","orcid":"0000-0002-2297-9614","position":10,"is_corresponding":false},{"id":1083,"name":"Steven A. Lubitz","orcid":"0000-0002-9599-4866","position":11,"is_corresponding":false},{"id":821388,"name":"Rachael A. Venn","orcid":"0000-0001-8608-2366","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Characteristics and Attitudes of Wearable Device Users and Nonusers in a Large Health Care System","abstract":"<jats:sec sec-type=\"background\" xml:lang=\"en\">\n            <jats:title>Background</jats:title>\n            <jats:p xml:lang=\"en\">Consumer wearable devices with health and wellness features are increasingly common and may enhance disease detection and management. Yet studies informing relationships between wearable device use, attitudes toward device data, and comprehensive clinical profiles are lacking.</jats:p>\n          </jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Methods and Results</jats:title>\n            <jats:p xml:lang=\"en\">WATCH‐IT (Wearable Activity Tracking for Comprehensive Healthcare‐Integrated Technology) studied adults receiving longitudinal primary or ambulatory cardiovascular care in the Mass General Brigham health care system from January 2010 to July 2021. Participants completed a 20‐question electronic survey about perceptions and use of consumer wearable devices, with responses linked to electronic health records. Multivariable logistic regression was used to identify factors associated with device use. Among 214 992 individuals receiving longitudinal primary or cardiovascular care with an active electronic portal, 11 121 responded (5.2%). Most respondents (55.8%) currently used a wearable device, and most nonusers (95.3%) would use a wearable if provided at no cost. Although most users (70.2%) had not shared device data with their doctor previously, most believed it would be very (20.4%) or moderately (34.4%) important to share device‐related health information with providers. In multivariable models, older age (odds ratio [OR], 0.80 per 10‐year increase [95% CI, 0.77–0.82]), male sex (OR, 0.87 [95% CI, 0.80–0.95]), and heart failure (OR, 0.75 [95% CI, 0.63–0.89]) were associated with lower odds of wearable device use, whereas higher median income (OR, 1.08 per 1‐quartile increase [95% CI, 1.04–1.12]) and care in a cardiovascular medicine clinic (OR, 1.17 [95% CI, 1.05–1.30]) were associated with greater odds of device use.</jats:p>\n          </jats:sec>\n          <jats:sec xml:lang=\"en\">\n            <jats:title>Conclusions</jats:title>\n            <jats:p xml:lang=\"en\">Among patients in primary and cardiovascular medicine clinics, consumer wearable device use is common, and most users perceive value in wearable health data.</jats:p>\n          </jats:sec>","is_dataset_classified":null,"base_score":2.8903717578961645,"endowment":2.8903717578961645,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"38156452","pmcid":"PMC10863832","openalex_id":"https://openalex.org/W4390405909","authors":[],"funders":[{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL092577","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"K01 HL148506","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL141434","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"U54 HL143541","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"K23 HL169839","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL139731","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"R33 HL158541","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"T32 HL007208","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL155343","title":null},{"funder_name":"NHLBI NIH HHS","grant_id":"R01 HL157635","title":null},{"funder_name":"National Institutes of Health","grant_id":"1U54HL143541-01","title":"The Center for Advancing Point of Care in Heart, Lung, Blood and Sleep Diseases"},{"funder_name":"National Institutes of Health","grant_id":"5T32HL007208-38","title":"Cell & Molecular Training for Cardiovascular Biology"},{"funder_name":"National Institutes of Health","grant_id":"4R33HL158541-02","title":"A phase I trial of AdKCNH2-G628S gene therapy for post-op atrial fibrillation"},{"funder_name":"National Institutes of Health","grant_id":"1R01HL157635-01A1","title":"Using Electrocardiogram Genetics to Inform Arrhythmia Risk"},{"funder_name":"National Institutes of Health","grant_id":"1R01HL139731-01","title":"Genomics of Cardiac Arrhythmias"},{"funder_name":"European Commission","grant_id":"965286","title":"Machine Learning Artificial Intelligence Early Detection Stroke Atrial Fibrillation"},{"funder_name":"National Institutes of Health","grant_id":"5R01HL155343-05","title":"SUPPORT-AF IV"},{"funder_name":"National Institutes of Health","grant_id":"5R01HL092577-02","title":"Identification of common genetic variants for atrial fibrillation and PR interval"},{"funder_name":"National Institutes of Health","grant_id":"5R01HL141434-02","title":"FHS-NEXT - Framingham Novel EXam using Technology"}],"total_grants":19,"fwci":6.2699,"citation_percentile":0.96904802,"influential_citations":0,"citation_trend":[{"year":2024,"count":2},{"year":2025,"count":12},{"year":2026,"count":3}],"oa_status":"gold","license":"cc-by-nc-nd","oa_locations":[{"url":"https://www.ahajournals.org/doi/pdf/10.1161/JAHA.123.032126","host_type":"journal"},{"url":"https://www.ahajournals.org/doi/pdf/10.1161/JAHA.123.032126","host_type":"publisher"},{"url":"https://www.ahajournals.org/doi/full/10.1161/JAHA.123.032126","host_type":"publisher"},{"url":"https://doi.org/10.1161/jaha.123.032126","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/38156452","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10863832","host_type":"repository"},{"url":"https://doaj.org/article/e0a1fc4fb94842e3a1659dba67069f3c","host_type":"repository"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10863832/pdf/JAH3-13-e032126.pdf","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC10863832","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC10863832?pdf=render","host_type":"Europe_PMC"},{"url":"http://dx.doi.org/10.1161/JAHA.123.032126","host_type":""}],"fields_of_study":["Mobile Health and mHealth Applications","Physical Activity and Health","Technology Use by Older Adults","03 medical and health sciences","0302 clinical medicine","Adult","Humans","Male","Wearable Electronic Devices","Surveys and Questionnaires","Electronic Health Records","Attitude","Delivery of Health Care"],"mesh_terms":["Wearable Electronic Devices","Adult","Attitude","Delivery of Health Care","Humans","Male","Surveys and Questionnaires","Electronic Health Records"],"keywords":["Wearable computer","Medicine","Wearable technology","Quartile","Odds","Health care","Odds ratio","Logistic regression","Family medicine","Gerontology","Confidence interval","Internal medicine","Computer science","Mobile Technologies","Health Care Innovation","Consumer Wearables","Adult","Male","Wearable Electronic Devices","Attitude","RC666-701","Surveys and Questionnaires","Diseases of the circulatory (Cardiovascular) system","Humans","Electronic Health Records","Delivery of Health Care","Original Research"],"sdg_mappings":[{"sdg_number":3,"sdg_label":"3. 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