{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T13:38:17Z","timestamp":1792849097818,"version":"4.5.0"},"reference-count":41,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["P30 AG017266"],"award-info":[{"award-number":["P30 AG017266"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Center for Demography of Health and Aging at the University of Wisconsin-Madison","id":[{"id":"https:\/\/ror.org\/01y2jtd41","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Current preventive screening reminders use generic due-date notifications that lack personalization. Targeted reminders allow personalized messages and resource allocation, yet the accuracy of behavioral forecasting with cholesterol screening behaviors remains unconfirmed. Therefore, this study aims to examine the accuracy of machine learning in predicting adults\u2019 future cholesterol screening behavior.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study included 8,288 participants from the Health and Retirement Study. Never receiving cholesterol screening over 12 years of follow-up (2007-2018) was identified as the target outcome. Predictors were constructed based on the Social-Ecological Model. Four machine learning (ML) algorithms were compared: logistic regression, random forests, gradient boosting machine (GBM), and eXtreme Gradient Boosting (XGBoost). Model performance was evaluated by Recall, Precision, and false-negative rate (FNR).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among the four ML algorithms, XGBoost performed best, with higher Recall (average: 0.8850) and the lowest FNR (0.1311), but suboptimal precision (average: 0.6228). The top five predictors were past cholesterol screening behavior, diagnosis of hypertension, osteoarthritis or rheumatoid arthritis, number of private insurance plans, and gender.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ML might be used to predict individuals\u2019 cholesterol screening behavior. Future research is needed to examine whether leveraging ML in targeted reminders might enhance cholesterol screening behaviors.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/14604582261500291","type":"journal-article","created":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T21:15:12Z","timestamp":1792530912000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting cholesterol screening behavior using machine learning: Social-ecological approach"],"prefix":"10.1177","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5658-6077","authenticated-orcid":false,"given":"Wan-Chin","family":"Kuo","sequence":"first","affiliation":[{"name":"University of Wisconsin-Madison"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingyu","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anthony D.","family":"McDonald","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingting","family":"Li","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jui-Hung","family":"Chang","sequence":"additional","affiliation":[{"name":"National Cheng Kung University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4916-3519","authenticated-orcid":false,"given":"Heather M.","family":"Johnson","sequence":"additional","affiliation":[{"name":"Christine E. Lynn Women\u2019s Health and Wellness Institute"},{"name":"Department of Cardiology, Charles E. Schmidt College of Medicine, Florida Atlantic University,"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,10,20]]},"reference":[{"key":"e_1_3_8_2_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehab484"},{"key":"e_1_3_8_3_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000001052"},{"key":"e_1_3_8_4_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2024.47902"},{"key":"e_1_3_8_5_2","first-page":"S11099666250014","article-title":"Rising atherosclerotic cardiovascular disease\u2013related mortality among older adults in the United States: a 22-year retrospective cohort study using the CDC WONDER database","author":"Maniya MT","year":"2025","unstructured":"Maniya MT, Siddiqi AK, Shahzad M, et al. Rising atherosclerotic cardiovascular disease\u2013related mortality among older adults in the United States: a 22-year retrospective cohort study using the CDC WONDER database. Hellenic Journal of Cardiology 2025: S1109966625001435, Published online July 2025. https:\/\/doi.org\/10.1016\/j.hjc.2025.06.001","journal-title":"Hellenic Journal of Cardiology"},{"key":"e_1_3_8_6_2","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.122.028205"},{"key":"e_1_3_8_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/S2214-109X(18)30275-4"},{"key":"e_1_3_8_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0733-8651(03)00080-8"},{"key":"e_1_3_8_9_2","doi-asserted-by":"publisher","DOI":"10.4103\/2230-8210.113753"},{"key":"e_1_3_8_10_2","doi-asserted-by":"publisher","DOI":"10.1097\/JCN.0000000000001364"},{"issue":"17","key":"e_1_3_8_11_2","first-page":"e1154","article-title":"2026 ACC\/AHA\/AACVPR\/ABC\/ACPM\/ADA\/AGS\/APhA\/ASPC\/NLA\/PCNA Guideline on the Management of Dyslipidemia: A Report of the American College of Cardiology\/American Heart Association Joint Committee on Clinical Practice Guidelines","volume":"153","author":"Writing CM","year":"2026","unstructured":"Writing CM, Blumenthal RS, Morris PB, et al. 2026 ACC\/AHA\/AACVPR\/ABC\/ACPM\/ADA\/AGS\/APhA\/ASPC\/NLA\/PCNA Guideline on the Management of Dyslipidemia: A Report of the American College of Cardiology\/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation 2026; 153(17): e1154, e1276. https:\/\/doi.org\/10.1161\/CIR.0000000000001423","journal-title":"Circulation"},{"key":"e_1_3_8_12_2","doi-asserted-by":"publisher","DOI":"10.1177\/20552076251356013"},{"key":"e_1_3_8_13_2","doi-asserted-by":"publisher","DOI":"10.3310\/hsdr02340"},{"key":"e_1_3_8_14_2","doi-asserted-by":"publisher","DOI":"10.3122\/jabfm.2024.240088R1"},{"key":"e_1_3_8_15_2","doi-asserted-by":"publisher","DOI":"10.1093\/jamia\/ocac242"},{"key":"e_1_3_8_16_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.117.032321"},{"key":"e_1_3_8_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.atherosclerosis.2017.10.006"},{"key":"e_1_3_8_18_2","doi-asserted-by":"publisher","DOI":"10.1002\/smi.3210"},{"key":"e_1_3_8_19_2","doi-asserted-by":"publisher","DOI":"10.34067\/KID.0000182021"},{"key":"e_1_3_8_20_2","doi-asserted-by":"publisher","DOI":"10.1097\/CEJ.0000000000000742"},{"key":"e_1_3_8_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.07.070"},{"key":"e_1_3_8_22_2","first-page":"361","article-title":"Examining Healthcare Utilization Patterns of Elderly Middle-Aged Adults in the United States","volume":"2016","author":"Zayas CE","year":"2016","unstructured":"Zayas CE, He Z, Yuan J, et al. Examining Healthcare Utilization Patterns of Elderly Middle-Aged Adults in the United States. Proc Int Fla AI Res Soc Conf 2016; 2016: 361\u2013366.","journal-title":"Proc Int Fla AI Res Soc Conf"},{"key":"e_1_3_8_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2025.105974"},{"key":"e_1_3_8_24_2","doi-asserted-by":"publisher","DOI":"10.1093\/workar\/wax032"},{"key":"e_1_3_8_25_2","doi-asserted-by":"publisher","DOI":"10.5993\/AJHB.38.1.14"},{"key":"e_1_3_8_26_2","doi-asserted-by":"publisher","DOI":"10.1080\/21645515.2018.1477458"},{"issue":"25","key":"e_1_3_8_27_2","first-page":"CIR000000000000","article-title":"AHA\/ACC\/AACVPR\/AAPA\/ABC\/ACPM\/ADA\/AGS\/APhA\/ASPC\/NLA\/PCNA Guideline on the Management of Blood Cholesterol","volume":"139","author":"Grundy SM","year":"2018","unstructured":"Grundy SM, Stone NJ, Bailey AL, et al. AHA\/ACC\/AACVPR\/AAPA\/ABC\/ACPM\/ADA\/AGS\/APhA\/ASPC\/NLA\/PCNA Guideline on the Management of Blood Cholesterol. Circulation 2018; 139(25): CIR0000000000000625. https:\/\/doi.org\/10.1161\/CIR.0000000000000625, Published online 10 November 2018.","journal-title":"Circulation"},{"key":"e_1_3_8_28_2","unstructured":"Health and Retirement Study. RAND HRS Longitudinal File 2020 (V2) Documentation. Published online. 2024. https:\/\/www.rand.org\/pubs\/tools\/TLA2097-1-v3.html"},{"key":"e_1_3_8_29_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12889-025-24748-z"},{"key":"e_1_3_8_30_2","doi-asserted-by":"publisher","DOI":"10.1186\/s41043-024-00596-2"},{"key":"e_1_3_8_31_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12888-023-05316-4"},{"key":"e_1_3_8_32_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1988.10478722"},{"key":"e_1_3_8_33_2","first-page":"238","volume-title":"Multiple imputation with Mplus","author":"Asparouhov T","year":"2010","unstructured":"Asparouhov T, Muth\u00e9n B. Multiple imputation with Mplus. MPlus Web Notes, 2010, pp. 238\u2013246. Published online."},{"key":"e_1_3_8_34_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-024-18426-2"},{"key":"e_1_3_8_35_2","doi-asserted-by":"publisher","DOI":"10.1007\/s40614-020-00270-y"},{"key":"e_1_3_8_36_2","doi-asserted-by":"publisher","DOI":"10.1175\/1520-0493(1950)078<0001:VOFEIT>2.0.CO;2"},{"key":"e_1_3_8_37_2","doi-asserted-by":"publisher","DOI":"10.1111\/cts.70056"},{"key":"e_1_3_8_38_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0304509"},{"key":"e_1_3_8_39_2","doi-asserted-by":"publisher","DOI":"10.3390\/en13205420"},{"key":"e_1_3_8_40_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11883-020-00843-x"},{"key":"e_1_3_8_41_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclinepi.2020.03.002"},{"key":"e_1_3_8_42_2","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2288-14-137"}],"container-title":["Health Informatics Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14604582261500291","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/14604582261500291","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14604582261500291","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T13:21:13Z","timestamp":1792848073000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/14604582261500291"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":41,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,10]]}},"alternative-id":["10.1177\/14604582261500291"],"URL":"https:\/\/doi.org\/10.1177\/14604582261500291","relation":{},"ISSN":["1460-4582","1741-2811"],"issn-type":[{"value":"1460-4582","type":"print"},{"value":"1741-2811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10]]},"article-number":"14604582261500291"}}