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      Digital Health Interventions in the Clinical Care and Treatment of Tuberculosis and HIV in Central Ethiopia: An Initial Provider Perceptions and Acceptability Study Using the Unified Theory of Acceptance and Use of Technology Model

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          Abstract

          Background:

          Digital health technologies are emerging as promising technologies to advance clinical care. This study aimed to assess providers’ perceptions and acceptability of digital health interventions (DHIs) in the clinical care and treatment of tuberculosis (TB) and HIV in Addis Ababa, Ethiopia.

          Methods:

          This was a multi-center, facility-based, mixed-method, cross-sectional study that included 14 government health-care facilities. The participants were health-care providers (HCPs) who provide TB and HIV clinical care. Using a tool framed by the unified theory of acceptance and use of technology model, data were collected. A linear regression model was used to assess the relationship between dependent and independent variables.

          Results:

          There were 76 HCPs actively engaged in HIV/TB clinical care services in the selected 14 study sites, of whom 60 met the inclusion criteria and participated in this study. The major factors that influence HCPs’ willingness to use different technologies were educational level (β = 0.097, t = 3.784, P = 0.006), age (β = −0.227, t = −1.757, P = 0.027), work experience (β = −0.366, t = −2.855, P = 0.016). The strongest facilitator of their acceptance and the use of the digital adherence technology were perceptions of positive performance expectancy.

          Conclusion:

          Many public healthcare facilities in Addis Ababa have already begun the process of implementing various DHIs and the level of acceptability of these technologies by HCPs was found to be high.

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          Most cited references33

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          The unified theory of acceptance and use of technology (UTAUT): a literature review

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            Artificial Intelligence in Medicine: Today and Tomorrow

            Artificial intelligence-powered medical technologies are rapidly evolving into applicable solutions for clinical practice. Deep learning algorithms can deal with increasing amounts of data provided by wearables, smartphones, and other mobile monitoring sensors in different areas of medicine. Currently, only very specific settings in clinical practice benefit from the application of artificial intelligence, such as the detection of atrial fibrillation, epilepsy seizures, and hypoglycemia, or the diagnosis of disease based on histopathological examination or medical imaging. The implementation of augmented medicine is long-awaited by patients because it allows for a greater autonomy and a more personalized treatment, however, it is met with resistance from physicians which were not prepared for such an evolution of clinical practice. This phenomenon also creates the need to validate these modern tools with traditional clinical trials, debate the educational upgrade of the medical curriculum in light of digital medicine as well as ethical consideration of the ongoing connected monitoring. The aim of this paper is to discuss recent scientific literature and provide a perspective on the benefits, future opportunities and risks of established artificial intelligence applications in clinical practice on physicians, healthcare institutions, medical education, and bioethics.
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              Digital adherence technologies for the management of tuberculosis therapy: mapping the landscape and research priorities

              Poor medication adherence may increase rates of loss to follow-up, disease relapse and drug resistance for individuals with active tuberculosis (TB). While TB programmes have historically used directly observed therapy (DOT) to address adherence, concerns have been raised about the patient burden, ethical limitations, effectiveness in improving treatment outcomes and long-term feasibility of DOT for health systems. Digital adherence technologies (DATs)—which include feature phone–based and smartphone-based technologies, digital pillboxes and ingestible sensors—may facilitate more patient-centric approaches for monitoring adherence, though available data are limited. Depending on the specific technology, DATs may help to remind patients to take their medications, facilitate digital observation of pill-taking, compile dosing histories and triage patients based on their level of adherence, which can facilitate provision of individualised care by TB programmes to patients with varied levels of risk. Research is needed to understand whether DATs are acceptable to patients and healthcare providers, accurate for measuring adherence, effective in improving treatment outcomes and impactful in improving health system efficiency. In this article, we describe the landscape of DATs that are being used in research or clinical practice by TB programmes and highlight priorities for research.
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                Author and article information

                Journal
                101615660
                42610
                Int J Mycobacteriol
                Int J Mycobacteriol
                International journal of mycobacteriology
                2212-5531
                2212-554X
                19 August 2022
                Jan-Mar 2022
                24 August 2022
                : 11
                : 1
                : 1-9
                Affiliations
                [1 ]Centre for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), College of Health Sciences, Addis Ababa University, Addis, Ababa,
                [2 ]Department of Public Health, Arsi University, College of Health Science, Asella, Ethiopia
                Author notes
                Address for correspondence: Mrs. Emnet Getachew, Addis Ababa University, College of Health Sciences, Centre for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), P.O. Box 9086, Addis Ababa, Ethiopia. emnet.getachew@ 123456aau.edu.et
                Author information
                http://orcid.org/0000-0002-6263-8283
                Article
                NIHMS1830774
                10.4103/ijmy.ijmy_235_21
                9400110
                35295017
                fb92e332-2bbb-4b14-897e-c31c3ba5f1b7

                This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.

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                digital health,electronic health,ethiopia technology,healthcare providers,human immunodeficiency virus,tuberculosis

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