53 research outputs found

    Impact of a community-based participatory research project with underserved communities at risk for hepatitis C virus in Ho Chi Minh City, Vietnam: an evaluation study

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    Background: Participatory approaches have become a widely applied research approach. Despite their popularity, there are many challenges associated with the evaluation of participatory projects. Here we describe an evaluation of a community-based participatory research study of underserved communities in Ho Chi Minh City (HCMC), Vietnam at risk for hepatitis C virus. The goals of our evaluation were to explore the main benefits and challenges of implementing and participating in a participatory study and to describe study impacts. Methods: We conducted two meetings with leaders and members of the participating groups followed by in-depth interviews with 10 participants. We then held a dissemination meeting with over 70 participants, including the representatives of each group, researchers from non-governmental organizations (community-based, national and international), and govenrment officials from the Vietnam Ministry of Health and the Department of Health of HCMC. Results: Results include four categories where we describe first the participatory impacts, followed by the collaborative impacts. Then we describe the benefits and challenges of creating and belonging to one of the groups, from members’ and leaders’ points of view. Finally, we describe the key suggestions that participants provided for future research. Conclusion: In conclusion, the evaluation approach led to both a research reflection on the ‘success’ of the project and enabled participants themselves to reflect on the outcomes and benefits of the study from their point of view

    Acceptance and user experiences of a wearable device for the management of hospitalized patients in COVID-19–designated wards in Ho Chi Minh City, Vietnam: action learning project

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    Background: Wearable devices have been used extensively both inside and outside of the hospital setting. During the COVID-19 pandemic, in some contexts, there was an increased need to remotely monitor pulse and saturated oxygen for patients due to the lack of staff and bedside monitors. Objective: A prototype of a remote monitoring system using wearable pulse oximeter devices was implemented at the Hospital for Tropical Diseases in Ho Chi Minh City, Vietnam, from August to December 2021. The aim of this work was to support the ongoing implementation of the remote monitoring system. Methods: We used an action learning approach with rapid pragmatic methods, including informal discussions and observations as well as a feedback survey form designed based on the technology acceptance model to assess the use and acceptability of the system. Based on these results, we facilitated a meeting using user-centered design principles to explore user needs and ideas about its development in more detail. Results: In total, 21 users filled in the feedback form. The mean technology acceptance model scores ranged from 3.5 (for perceived ease of use) to 4.4 (for attitude) with behavioral intention (3.8) and perceived usefulness (4.2) scoring in between. Those working as nurses scored higher on perceived usefulness, attitude, and behavioral intention than did physicians. Based on informal discussions, we realized there was a mismatch between how we (ie, the research team) and the ward teams perceived the use and wider purpose of the technology. Conclusions: Designing and implementing the devices to be more nurse-centric from their introduction could have helped to increase their efficiency and use during the complex pandemic period

    Achieving Bangladesh's Tourism Potential: Linkages to Export Diversification, Employment Generation and the 'Green Economy'

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    Bangladesh's international image is not as a popular tourism destination, and many people might be surprised to learn it has three World Heritage sites, including the Sundarbans tiger reserves. Moreover, it is part of important travel circuits for cultural and religious tourism, and has demonstrated potential for sports tourism. The objective of this working paper is to critically test the assertion that pro-poor "green" tourism is one of the best development options for the majority of least developed countries (LDCs) - a challenging task in Bangladesh in the face of the country's success as an exporter of readymade garments - by comparing tourism to the available alternatives with regard to the crucial government priorities of export diversification, employment generation and the "green economy". It is well-known that Bangladesh is under strong pressure to diversify its exports, to generate new employment (especially in rural areas), and to respond to critical environmental issues. The government has identified over 30 "thrust sectors" (including tourism) to help address these challenges, but otherwise tourism is rarely mentioned as a major trade and development option for Bangladesh. Within the limitations of data availability, this working paper reaches the conclusion that greater efforts to develop "green" tourism would be highly beneficial for facilitating rural development, environmental and cultural protection, gender equality, and export diversification in services. The most obvious current impediments are inadequate infrastructure, lack of investment and (typically election year) political conflict, but behind these factors appear to be a serious lack of stakeholder coordination, insufficient regulatory and administrative transparency and coherence, as well as some government reluctance to relinquish greater commercial autonomy in tourism to the private sector. This paper offers extensive analysis and some suggestions to help address the impediments, including the recommendation to create a Bangladesh Tourism Stakeholders Forum

    Clinical benefit of AI-assisted lung ultrasound in a resource-limited intensive care unit

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    BackgroundInterpreting point-of-care lung ultrasound (LUS) images from intensive care unit (ICU) patients can be challenging, especially in low- and middle- income countries (LMICs) where there is limited training available. Despite recent advances in the use of Artificial Intelligence (AI) to automate many ultrasound imaging analysis tasks, no AI-enabled LUS solutions have been proven to be clinically useful in ICUs, and specifically in LMICs. Therefore, we developed an AI solution that assists LUS practitioners and assessed its usefulness in a low resource ICU.MethodsThis was a three-phase prospective study. In the first phase, the performance of four different clinical user groups in interpreting LUS clips was assessed. In the second phase, the performance of 57 non-expert clinicians with and without the aid of a bespoke AI tool for LUS interpretation was assessed in retrospective offline clips. In the third phase, we conducted a prospective study in the ICU where 14 clinicians were asked to carry out LUS examinations in 7 patients with and without our AI tool and we interviewed the clinicians regarding the usability of the AI tool.ResultsThe average accuracy of beginners' LUS interpretation was 68.7% [95% CI 66.8-70.7%] compared to 72.2% [95% CI 70.0-75.6%] in intermediate, and 73.4% [95% CI 62.2-87.8%] in advanced users. Experts had an average accuracy of 95.0% [95% CI 88.2-100.0%], which was significantly better than beginners, intermediate and advanced users (p < 0.001). When supported by our AI tool for interpreting retrospectively acquired clips, the non-expert clinicians improved their performance from an average of 68.9% [95% CI 65.6-73.9%] to 82.9% [95% CI 79.1-86.7%], (p < 0.001). In prospective real-time testing, non-expert clinicians improved their baseline performance from 68.1% [95% CI 57.9-78.2%] to 93.4% [95% CI 89.0-97.8%], (p < 0.001) when using our AI tool. The time-to-interpret clips improved from a median of 12.1 s (IQR 8.5-20.6) to 5.0 s (IQR 3.5-8.8), (p < 0.001) and clinicians' median confidence level improved from 3 out of 4 to 4 out of 4 when using our AI tool.ConclusionsAI-assisted LUS can help non-expert clinicians in an LMIC ICU improve their performance in interpreting LUS features more accurately, more quickly and more confidently

    Astrocytes, Microglia, and Parkinson’s Disease

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    Astrocytes and microglia support well-being and well-function of the brain through diverse functions in both intact and injured brain. For example, astrocytes maintain homeostasis of microenvironment of the brain through up-taking ions and neurotransmitters, and provide growth factors and metabolites for neurons, etc. Microglia keep surveying surroundings, and remove abnormal synapses or respond to injury by isolating injury sites and expressing inflammatory cytokines. Therefore, their loss and/or functional alteration may be directly linked to brain diseases. Since Parkinson's disease (PD)-related genes are expressed in astrocytes and microglia, mutations of these genes may alter the functions of these cells, thereby contributing to disease onset and progression. Here, we review the roles of astrocytes and microglia in intact and injured brain, and discuss how PD genes regulate their functions
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