Digital Health and Artificial Intelligence: Advancing Healthcare Provision in Latin America

Alonso, Roberto García; Thoene, Ulf; Benavides, Diego Davila

doi:10.1109/mitp.2022.3143530

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…Since the releases of Aarogya Setu multiple security concerns were raised such as, who the developer of the app is, its source code, how much data is tracked, who will be the owner of the data and what will happen with the data. Often citizens do not want to share personal activities and information with the government (Tang et al , 2021) such concerns are common especially for finance and healthcare apps (García Alonso et al , 2022), which might be the reason for nonadoption of Aarogya Setu. Studies also highlight that better-educated individuals experience increasing decline in political trust, which is more driven by their changing expectations than the government’s failure (Dalton, 2005).…”

Section: Discussionmentioning

confidence: 99%

A meso-level exploration of citizen’s mGov adoption from SD logic perspective: the case of COVID-19 tracking app of India

Sharma¹,

Pandey

2023

DPRG

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Purpose This study aims to explore the factors affecting the adoption of mGov apps using the theoretical foundations of service-dominant (SD) logic. The authors specifically explore the impact of resource distribution (infrastructure and knowledge) and environmental variables (health infrastructure) among the Indian states on the adoption of Aarogya Setu (the COVID-19 tracking app) by their citizens. Design/methodology/approach For the meso-level study, the states of India are the unit of analysis. The authors have used secondary data published by the government and other reliable organizations. The study is based on 29 states of India and Delhi, a union territory and the capital of India. The authors conducted a regression and moderation analysis using SPSS and PROCESS macros on the collected secondary data. Findings The findings reveal that operand resources (state domestic productivity per capita and internet penetration rate) positively impact the adoption of the mGov app. The operant resource (literacy) and the environmental variable (health index) are, however, negatively affecting the adoption of the mGov app. On the other hand, another operant resource, digital literacy, was found to have no significant effect on the adoption of the mGov app. Further, the moderating variable, health index, is found to be moderating all the relationships except internet penetration and adoption of the mGov app. Originality/value The study is novel in two aspects. First, in using the theoretical foundation of SD logic to examine the factors impacting the adoption of mGov app. Second, it is a meso-level study, which is not a widely explored avenue in mGov research.

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Section: Discussionmentioning

confidence: 99%

A meso-level exploration of citizen’s mGov adoption from SD logic perspective: the case of COVID-19 tracking app of India

Sharma¹,

Pandey

2023

DPRG

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“…Moreover, there are concerns regarding privacy and transparency in the use of patient data, which are exacerbated by the absence of strong regulatory frameworks and data protection laws. The technological and regulatory di culties faced in implementing AI-based services could hinder their adoption and limit the bene ts that AI could bring to healthcare systems in Somalia [31]. This study aimed to investigate the level of knowledge, attitudes, and practices of AI among healthcare professionals in Somalia as well as their familiarity with different AI technologies and practices.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Knowledge, Attitudes, and Practices in Artificial Intelligence Among Healthcare Professionals in Mogadishu, Somalia

Ahmed,

Dirie,

Mohamud

et al. 2024

Preprint

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Background: The rapid advancement of artificial intelligence (AI) in various sectors has revolutionized problem-solving approaches, particularly in healthcare. Developed countries have invested significantly in AI research and applications in healthcare, while low-income countries such as Somalia lag due to various challenges. This study aimed to assess the knowledge, attitudes, and practices (KAP) of AI among healthcare professionals in Somalia and explore their familiarity with AI technologies and practices. Methods: A cross-sectional study was conducted from January 1, 2024, to March 15, 2024, among 441 healthcare professionals in Somalia, using an online questionnaire. The questionnaire assessed the participants' sociodemographic information, knowledge of AI applications in healthcare, attitudes towards AI capabilities, and practical experience with AI in healthcare. Results: Most participants demonstrated good knowledge of AI (67.6%) and a positive attitude towards its potential in healthcare (80.5%). However, a significant gap was observed in the practical application of AI, with 79.1% of the respondents reporting poor practice. The study also found that sociodemographic factors such as age, gender, and income level did not significantly influence knowledge or attitudes towards AI but did affect its practical use. Professionals in certain fields such as midwifery and public health are more likely to use AI in their work. Knowledge and attitude scores were also significant predictors of practice scores. Conclusion: Healthcare professionals in Somalia demonstrate a good understanding and positive attitudes towards AI but encounter challenges in its practical application. This study emphasizes the necessity of an enhanced infrastructure, technical expertise, and data access to fully utilize AI's potential in healthcare. It also highlights the significance of addressing ethical considerations and implementing regulations to ensure responsible use of AI in healthcare. Efforts are needed to translate awareness and receptiveness into effective practice, which could result in a better healthcare system.

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Users’ Experiences of Algorithm-Mediated Public Services: Folk Theories, Trust, and Strategies in the Global South

López,

Davidoff,

Luco

et al. 2024

International Journal of Human–Computer Interaction

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Digital Health and Artificial Intelligence: Advancing Healthcare Provision in Latin America

Cited by 5 publications

References 8 publications

A meso-level exploration of citizen’s mGov adoption from SD logic perspective: the case of COVID-19 tracking app of India

A meso-level exploration of citizen’s mGov adoption from SD logic perspective: the case of COVID-19 tracking app of India

Assessment of Knowledge, Attitudes, and Practices in Artificial Intelligence Among Healthcare Professionals in Mogadishu, Somalia

Users’ Experiences of Algorithm-Mediated Public Services: Folk Theories, Trust, and Strategies in the Global South

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