Leveraging AI and Technology for Holistic Asthma Management in the Pasifika Community
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Mirza, Farhaan
Jayamini, Widana Kankanamge Darsha
Lutui, Raymond
Pole, Kalesita
Matenga-Ikihele, Amio
Mu’aulama, Arieta Fa’apesolo
Chan, Amy Hai Yan
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Elsevier BV
Abstract
Asthma is a major health concern for Pasifika in New Zealand (NZ). This study explores the perspectives of Pasifika in NZ regarding the use of technology and Artificial Intelligence (AI) for asthma management. This study employed a qualitative research design, using purposive sampling to recruit eighteen Pasifika participants diagnosed with asthma. Data were analyzed using a general inductive approach. Six core themes were identified: (1) Awareness of AI; (2) Potential of AI; (3) Concerns of AI; (4) Digital divide in age groups; (5) General asthma management; and (6) Future design considerations. A holistic framework is postulated to enhance Pasifika asthma care using technology and AI. This study contributes to the sparse literature on Pasifika perspectives regarding AI-driven asthma management. Effective implementation requires ensuring accuracy, protecting privacy, improving access, and supporting families to confidently manage asthma. A balanced approach integrating technology with personal management is the key to effective asthma management.
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46 Information and Computing Sciences, 4608 Human-Centred Computing, Machine Learning and Artificial Intelligence, Networking and Information Technology R&D (NITRD), Asthma, Lung, Respiratory, 3 Good Health and Well Being, Artificial intelligence, Digital technology, Asthma care, Digital health, Pacific Islanders
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Telematics and Informatics Reports, ISSN: 2772-5030 (Print), Elsevier BV, 21, 100302-100302. doi: 10.1016/j.teler.2026.100302
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© 2026 The Authors. Published by Elsevier B.V. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.
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Except where otherwise noted, this item's license is described as © 2026 The Authors. Published by Elsevier B.V. This is an open access article distributed under the terms of the Creative Commons CC-BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. You are not required to obtain permission to reuse this article.