{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T15:27:16Z","timestamp":1787412436536,"version":"build-2736575974"},"reference-count":43,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T00:00:00Z","timestamp":1787270400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"NHMRC Centre of Research Excellence (CRE) for mitigating airborne threats to health","award":["RG203873"],"award-info":[{"award-number":["RG203873"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["HIM J"],"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Mobile applications for infectious disease surveillance can facilitate early outbreak detection and timely public health action. However, there is limited information about their real-world adoption, public trust, perceived usefulness, and preferred features.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>To assess public trust, usability, and adoption of infectious disease surveillance mobile apps and to identify the features preferred by the public.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method:<\/jats:title>\n                    <jats:p>An anonymous, online, cross-sectional survey was conducted across Australia between May and August 2024. A total of 5177 adults aged\u2009\u2a7e\u200918\u2009years completed the survey. Descriptive statistics and multivariable logistic regression analyses examined sociodemographic correlates of mobile app use, trust, and perceived usefulness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Use of infectious disease surveillance apps was low, with only 151 participants (2.9%) reporting prior use. Despite this, 60% (3122\/5177) perceived such apps as useful, and 15% (790\/5177) reported trust in them. Younger adults were significantly more likely to use and trust these apps than older adults. Occupation in a health-related field (Odds ratio [OR] 1.89; 95% Confidence interval [CI] 1.21, 2.93), frontline responder status (OR 3.33; 95% CI 1.86, 5.96), postgraduate education (OR 2.04; 95% CI 1.20, 3.46), and speaking a non-English language at home (OR 2.72; 95% CI 1.50, 4.91) were significant predictors of app use. Men reported greater trust (OR 1.20; 95% CI 1.01, 1.43) but lower perceived usefulness (OR 0.81; 95% CI 0.72, 0.92) than women. Participants most frequently preferred features providing real-time updates and affected-area maps.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Although most participants perceived mobile apps to be useful, their adoption was low. Use may vary over time and increase during pandemics, severe epidemics, or travel. Trust diverged from perceived usefulness in specific groups, and sustained use clustered with greater confidence. Design and implementation of infectious disease surveillance apps should emphasise high-value features, language equity, targeted onboarding for older adults, and strategies that convert trust into perceived usefulness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Implications for health information management practice:<\/jats:title>\n                    <jats:p>These findings highlight the need to integrate trust, usability, and accessibility into app design. Prioritising user-centred interfaces, language inclusivity, and transparent data practices in all facets of healthcare services, including the management of health information, can enhance engagement, improve data quality, and support effective digital disease surveillance. The health information manager\u2019s skillset would be essential for informing the successful integration of mobile health app data into electronic medical or health record systems.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/18333583261452982","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T10:21:14Z","timestamp":1787307674000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Attitudes toward mobile apps for infectious disease surveillance: a cross-sectional study of trust, usability, and adoption in Australia"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-3848-6097","authenticated-orcid":false,"given":"Fatema","family":"Kalyar","sequence":"first","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chandini Raina","family":"Maclntyre","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"},{"name":"Arizona State University, Tempe, AZ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohana","family":"Kunasekaran","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Poulos","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charitha","family":"de Silva","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Helen","family":"Skouteris","sequence":"additional","affiliation":[{"name":"Monash University in Collaboration with Monash Health, Melbourne, VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abrar Ahmad","family":"Chughtai","sequence":"additional","affiliation":[{"name":"University of New South Wales, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,8,21]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"crossref","unstructured":"Adnan A Irvine RE Williams A et al. (2025) Improving acceptability of mHealth apps\u2014The use of the technology acceptance model to assess the acceptability of mHealth apps: Systematic review. Journal of Medical Internet Research 27: e66432. https:\/\/doi.org\/10.2196\/66432","DOI":"10.2196\/66432"},{"key":"e_1_3_3_3_1","unstructured":"Australian Digital Health Agency (2022) Assessment Framework for mHealth Apps. Available at: https:\/\/www.digitalhealth.gov.au\/about-us\/strategies-and-plans\/assessment-framework-for-mhealth-apps (accessed 6 June 2025)."},{"key":"e_1_3_3_4_1","doi-asserted-by":"crossref","unstructured":"Berry I Soucy J-PR Tuite A et al. (2020) Open access epidemiologic data and an interactive dashboard to monitor the COVID-19 outbreak in Canada. Canadian Medical Association Journal 192(15): E420. https:\/\/doi.org\/10.1503\/cmaj.75262","DOI":"10.1503\/cmaj.75262"},{"key":"e_1_3_3_5_1","doi-asserted-by":"crossref","unstructured":"Bile Hassan I Murad MA El-Shekeil I et al. (2022) Extending the UTAUT2 model with a privacy calculus model to enhance the adoption of a health information application in Malaysia. Informatics 9: 31. https:\/\/doi.org\/10.3390\/informatics9020031","DOI":"10.3390\/informatics9020031"},{"key":"e_1_3_3_6_1","doi-asserted-by":"crossref","unstructured":"Burdon M Wang B (2021) Implementing COVIDSafe: The role of trustworthiness and information privacy law. Law Technology and Humans 3(1): 35\u201350. https:\/\/doi.org\/10.5204\/lthj.1808","DOI":"10.5204\/lthj.1808"},{"key":"e_1_3_3_7_1","doi-asserted-by":"crossref","unstructured":"Byambasuren O Beller E Glasziou P (2019) Current knowledge and adoption of mobile health apps among Australian general practitioners: Survey study. JMIR Mhealth Uhealth 7(6): e13199. https:\/\/doi.org\/10.2196\/13199","DOI":"10.2196\/13199"},{"key":"e_1_3_3_8_1","doi-asserted-by":"crossref","unstructured":"Catapan SC Sazon H Zheng S et al. (2025) A systematic review of consumers\u2019 and healthcare professionals\u2019 trust in digital healthcare. NPJ Digital Medicine 8(1): 115. https:\/\/doi.org\/10.1038\/s41746-025-01510-8","DOI":"10.1038\/s41746-025-01510-8"},{"key":"e_1_3_3_9_1","doi-asserted-by":"crossref","unstructured":"Chelberg GR Butten K Mahoney R (2022) Culturally safe eHealth interventions with aboriginal and Torres Strait Islander people: Protocol for a best practice framework. JMIR Research Protocols 11(6): e34904. https:\/\/doi.org\/10.2196\/34904","DOI":"10.2196\/34904"},{"key":"e_1_3_3_10_1","unstructured":"CSIRO (2024) Digital Health Research can be Positive for Indigenous People. But our Study Found it Needs to Follow these Principles. Available at: https:\/\/www.csiro.au\/en\/news\/All\/Articles\/2024\/September\/Digital-health-research-Indigenous (accessed 16 August 2025)."},{"key":"e_1_3_3_11_1","doi-asserted-by":"crossref","unstructured":"Dalton CB Carlson SJ Butler MT et al. (2017) Insights from Flutracking: Thirteen tips to growing a web-based participatory surveillance system. JMIR Public Health and Surveillance 3(3): e48. https:\/\/doi.org\/10.2196\/publichealth.7333","DOI":"10.2196\/publichealth.7333"},{"key":"e_1_3_3_12_1","unstructured":"Department of Health and Aged Care (2024) The Digital Health Blueprint and Action Plan 2023\u20132033. Available at: https:\/\/www.health.gov.au\/sites\/default\/files\/2024-01\/the-digital-health-blueprint-and-action-plan-2023-2033_0.pdf (accessed 6 June 2025)."},{"key":"e_1_3_3_13_1","unstructured":"Dynata (2024) Dynata. Available at: https:\/\/www.dynata.com\/ (accessed 5 May 2024)."},{"key":"e_1_3_3_14_1","doi-asserted-by":"crossref","unstructured":"Field E Dyda A Hewett M et al. (2021) Development of the COVID-19 real-time information system for preparedness and epidemic response (CRISPER) Australia. Frontiers in Public Health 9: 753493. https:\/\/doi.org\/10.3389\/fpubh.2021.753493","DOI":"10.5694\/mja2.51019"},{"key":"e_1_3_3_15_1","unstructured":"FluTracking (2025) FluTracking Weekly Report: Latest (Australia). Available at: https:\/\/www.flutracking.net\/Info\/Report\/Latest\/AU (accessed 16 August 2025)."},{"key":"e_1_3_3_16_1","doi-asserted-by":"crossref","unstructured":"Guerrisi C Turbelin C Blanchon T et al. (2016) Participatory syndromic surveillance of influenza in Europe. Journal of Infectious Diseases 214(Suppl. 4): S386\u2013S392. https:\/\/doi.org\/10.1093\/infdis\/jiw280","DOI":"10.1093\/infdis\/jiw280"},{"key":"e_1_3_3_17_1","doi-asserted-by":"crossref","unstructured":"Henson C Chapman F Shepherd G et al. (2022) Mature aged Aboriginal and Torres Strait Islander adults are using digital health technologies. Digital Health 8: 20552076221145846. https:\/\/doi.org\/10.1177\/20552076221145846","DOI":"10.1177\/20552076221145846"},{"key":"e_1_3_3_18_1","doi-asserted-by":"crossref","unstructured":"Jezrawi R Balakumar S Masud R et al. (2022) Patient and physician perspectives on the use and outcome measures of mHealth apps: Exploratory survey and focus group study. Digital Health 8: 20552076221102773. https:\/\/doi.org\/10.1177\/20552076221102773","DOI":"10.1177\/20552076221102773"},{"key":"e_1_3_3_19_1","doi-asserted-by":"crossref","unstructured":"Kendall M Ferretti L Wymant C et al. (2024) Drivers of epidemic dynamics in real time from daily digital COVID-19 measurements. Science 385(6710): eadm8103. https:\/\/doi.org\/10.1126\/science.adm8103","DOI":"10.1126\/science.adm8103"},{"key":"e_1_3_3_20_1","doi-asserted-by":"crossref","unstructured":"Khatri RB Assefa Y (2022) Access to health services among culturally and linguistically diverse populations in the Australian universal health care system: Issues and challenges. BMC Public Health 22(1): 880. https:\/\/doi.org\/10.1186\/s12889-022-13256-z","DOI":"10.1186\/s12889-022-13256-z"},{"key":"e_1_3_3_21_1","doi-asserted-by":"crossref","unstructured":"Koppeschaar C Colizza V Guerrisi C et al. (2017) Influenzanet: Citizens among 10 countries collaborating to monitor influenza in Europe. JMIR Public Health and Surveillance 3(3): e66. https:\/\/doi.org\/10.2196\/publichealth.7429","DOI":"10.2196\/publichealth.7429"},{"key":"e_1_3_3_22_1","doi-asserted-by":"crossref","unstructured":"McGowan CR Takahashi E Romig L et al. (2022) Community-based surveillance of infectious diseases: A systematic review of drivers of success. BMJ Global Health 7(8): e009934. https:\/\/doi.org\/10.1136\/bmjgh-2022-009934","DOI":"10.1136\/bmjgh-2022-009934"},{"key":"e_1_3_3_23_1","doi-asserted-by":"crossref","unstructured":"Moschonis G Siopis G Jung J et al. (2023) Effectiveness reach uptake and feasibility of digital health interventions for adults with type 2 diabetes: A systematic review and meta-analysis of randomised controlled trials. The Lancet Digital Health 5(3): e125\u2013e143. https:\/\/doi.org\/10.1016\/S2589-7500(22)00233-3","DOI":"10.1016\/S2589-7500(22)00233-3"},{"key":"e_1_3_3_24_1","unstructured":"Office of the Australian Information Commissioner (2025) Australian Privacy Principles (APPs). Available at: https:\/\/www.oaic.gov.au\/privacy\/australian-privacy-principles (accessed 6 July 2025)."},{"key":"e_1_3_3_25_1","doi-asserted-by":"crossref","unstructured":"Ortega P Miller De Rutt\u00e9 A Vela M (2025) Language equity in health technology for patients with non\u2013English language preference. JAMA Network Open 8(2): e2457424. https:\/\/doi.org\/10.1001\/jamanetworkopen.2024.57424","DOI":"10.1001\/jamanetworkopen.2024.57424"},{"key":"e_1_3_3_26_1","doi-asserted-by":"crossref","unstructured":"Patrik S Achim H Elske A (2022) Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: A cross-sectional validation study. BMJ Health & Care Informatics 29(1): e100640. https:\/\/doi.org\/10.1136\/bmjhci-2022-100640","DOI":"10.1136\/bmjhci-2022-100640"},{"key":"e_1_3_3_27_1","unstructured":"Pearcey F (2020) The COVIDSafe App: A Question of Trust. Available at: https:\/\/www.pearcey.org.au\/initiatives\/public-policy\/the-covidsafe-app-a-question-of-trust\/pearcey-covidsafe-app-paper\/ (accessed 6 July 2025)."},{"key":"e_1_3_3_28_1","doi-asserted-by":"crossref","unstructured":"Quinn E Hsiao KH Maitland-Scott I et al. (2021) Web-based apps for responding to acute infectious disease outbreaks in the community: Systematic review. JMIR Public Health and Surveillance 7(4): e24330. https:\/\/doi.org\/10.2196\/24330","DOI":"10.2196\/24330"},{"key":"e_1_3_3_29_1","doi-asserted-by":"crossref","unstructured":"Rasi S (2020) Impact of language barriers on access to healthcare services by immigrant patients: A systematic review. Asia Pacific Journal of Health Management 15(1): 35\u201348. https:\/\/doi.org\/10.24083\/apjhm.v15i1.271","DOI":"10.24083\/apjhm.v15i1.271"},{"key":"e_1_3_3_30_1","doi-asserted-by":"crossref","unstructured":"Schomakers E-M Lidynia C Vervier LS et al. (2022) Applying an extended UTAUT2 model to explain user acceptance of lifestyle and therapy mobile health apps: Survey study. JMIR Mhealth Uhealth 10(1): e27095. https:\/\/doi.org\/10.2196\/27095","DOI":"10.2196\/27095"},{"key":"e_1_3_3_31_1","doi-asserted-by":"crossref","unstructured":"Silvera-Tawil D Pocock C Bradford D et al. (2021) Enabling nurse-patient communication with a mobile app: Controlled pretest-posttest study with nurses and non\u2013English-speaking patients. JMIR Nursing 4(3): e19709. https:\/\/doi.org\/10.2196\/19709","DOI":"10.2196\/19709"},{"key":"e_1_3_3_32_1","unstructured":"Sleep S (2025) Australian Smartphone Statistics. Available at: https:\/\/www.sleepsociety.com.au\/blog\/australian-smartphone-statistics (accessed 6 July 2025)."},{"key":"e_1_3_3_33_1","doi-asserted-by":"crossref","unstructured":"Soh SE Ayton D Bevins A et al. (2024) Attitudes and behaviours regarding COVID-19 mitigation strategies in Australians with an underlying health condition: A cross-sectional study. Health Expectations 27: e70025. https:\/\/doi.org\/10.1111\/hex.70025","DOI":"10.1111\/hex.70025"},{"key":"e_1_3_3_34_1","doi-asserted-by":"publisher","DOI":"10.2196\/23081"},{"key":"e_1_3_3_35_1","unstructured":"UNSW Sydney (2024) Placing Australia at the Forefront of Digital Public Health. Available at: https:\/\/www.unsw.edu.au\/news\/2024\/12\/placing-australia-at-the-forefront-of-digital-public-health (accessed 6 July 2025)."},{"key":"e_1_3_3_36_1","doi-asserted-by":"crossref","unstructured":"Venkatesh V Thong JYL Xu X (2012) Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly 36(1): 157\u2013178. https:\/\/doi.org\/10.2307\/41410412","DOI":"10.2307\/41410412"},{"key":"e_1_3_3_37_1","doi-asserted-by":"crossref","unstructured":"Vogt F Haire B Selvey L et al. (2022) Effectiveness evaluation of digital contact tracing for COVID-19 in New South Wales Australia. The Lancet Public Health 7(3): e250\u2013e258. https:\/\/doi.org\/10.1016\/S2468-2667(22)00010-X","DOI":"10.1016\/S2468-2667(22)00010-X"},{"key":"e_1_3_3_38_1","doi-asserted-by":"crossref","unstructured":"Von Wyl V (2025) Improving digital study designs: Better metrics systematic reporting and an engineering mindset. The Lancet Digital Health 7(1): e4\u2013e5. https:\/\/doi.org\/10.1016\/S2589-7500(24)00244-9","DOI":"10.1016\/S2589-7500(24)00244-9"},{"key":"e_1_3_3_39_1","doi-asserted-by":"crossref","unstructured":"Walraven G Theodoratou J Shi T (2023) Characteristics of participatory surveillance systems for influenza-like illness: A systematic review. Journal of Global Health 13: 04130. https:\/\/doi.org\/10.7189\/jogh.13.04130","DOI":"10.7189\/jogh.13.04130"},{"key":"e_1_3_3_40_1","doi-asserted-by":"crossref","unstructured":"Wong AKC Wong FKY Chow KKS et al. (2022) Effect of a mobile health application with Nurse support on quality of life among community-dwelling older adults in Hong Kong: A randomized clinical trial. JAMA Network Open 5(11): e2241137. https:\/\/doi.org\/10.1001\/jamanetworkopen.2022.41137","DOI":"10.1001\/jamanetworkopen.2022.41137"},{"key":"e_1_3_3_41_1","unstructured":"World Health Organization (WHO) (2019) Recommendations on Digital Interventions for Health System Strengthening. Available at: https:\/\/www.who.int\/publications\/i\/item\/9789241550505 (accessed 16 August 2025)."},{"key":"e_1_3_3_42_1","unstructured":"World Health Organization (WHO) (2024a) Best Practices for the Design Implementation Analysis and Reporting of Participatory Surveillance Systems for Influenza and ILI. Available at: https:\/\/www.who.int\/publications\/i\/item\/9789240095038 (accessed 16 August 2025)."},{"key":"e_1_3_3_43_1","unstructured":"World Health Organization (WHO) (2024b) Putting Participatory Surveillance into Practice: New WHO Publication Released. Available at: https:\/\/www.who.int\/news\/item\/16-10-2024-putting-participatory-surveillance-into-practice\u2014new-who-publication-released (accessed 16 August 2025)."},{"key":"e_1_3_3_44_1","doi-asserted-by":"crossref","unstructured":"Wu Y Ye Q Shen F et al. (2022) Country- and app-level factors affecting the adoption and evaluation of COVID-19 mobile apps. BMC Public Health 22(1): 2457. https:\/\/doi.org\/10.1186\/s12889-022-14918-8","DOI":"10.1186\/s12889-022-14918-8"}],"container-title":["Health Information Management Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18333583261452982","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/18333583261452982","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/18333583261452982","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,22]],"date-time":"2026-08-22T15:16:41Z","timestamp":1787411801000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/18333583261452982"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,21]]},"references-count":43,"alternative-id":["10.1177\/18333583261452982"],"URL":"https:\/\/doi.org\/10.1177\/18333583261452982","relation":{},"ISSN":["1833-3583","1833-3575"],"issn-type":[{"value":"1833-3583","type":"print"},{"value":"1833-3575","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,21]]},"article-number":"18333583261452982"}}