{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T09:08:15Z","timestamp":1774429695627,"version":"3.50.1"},"reference-count":99,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T00:00:00Z","timestamp":1742515200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Woosong University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Digital"],"abstract":"<jats:p>Mobile Health (mHealth) technologies are transforming healthcare by making it more accessible, efficient, and patient-centric. This study investigates the factors influencing Millennial\u2019s mobile health adoption intention (mHAI). We propose a research model based on the integrated model of the Unified Theory of Acceptance and Use of Technology\u2014UTAUT and the health belief model\u2014HBM. A cross-sectional study was carried out employing purposive sampling to enlist Generation Y (born between 1981 and 1996) and 220 valid questionnaires were collected. We employed structure equation modeling partial least square (SEM-PLS) along with artificial neural network (ANN) and importance\u2013performance map analysis (IPMA) to analyze our model. The research findings revealed that performance expectancy is the most influential factor, while effort expectancy showed no significant association with mHAI. Theoretical and managerial implications are offered to expand the literature on digital healthcare studies, indicating how healthcare providers in developing countries can attract their potential users.<\/jats:p>","DOI":"10.3390\/digital5020009","type":"journal-article","created":{"date-parts":[[2025,3,21]],"date-time":"2025-03-21T09:09:07Z","timestamp":1742548147000},"page":"9","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Revealing Factors Influencing mHealth Adoption Intention Among Generation Y: An Empirical Study Using SEM-ANN-IPMA Analysis"],"prefix":"10.3390","volume":"5","author":[{"given":"Ashikur","family":"Rahman","sequence":"first","affiliation":[{"name":"Department of Information Technology and Management, Daffodil International University, Dhaka 1207, Bangladesh"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3403-4095","authenticated-orcid":false,"given":"Jia","family":"Uddin","sequence":"additional","affiliation":[{"name":"AI and Big Data Department, Endicott College, Woosong University, Daejeon 34606, Republic of Korea"}]}],"member":"1968","published-online":{"date-parts":[[2025,3,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1108\/OIR-01-2015-0007","article-title":"Determinants of adoption of mobile health services","volume":"39","author":"Lee","year":"2015","journal-title":"Online Inf. 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