Search Results (3)

Objective: African Americans (AAs) carry the largest burden for almost every type of cancer in the US and are also more likely to die from cancer. Approximately 10% of cancers can be explained by a hereditary factor and detected earlier. Many AAs, however, have inequitable access to hereditary cancer risk assessment (HCRA) tools and information, further exacerbating disparities in cancer rates. Innovative communication strategies to promote community-based HCRA information have promise as a means encouraging optimal primary cancer screening among AAs. The current pilot study followed a participatory process where researchers engaged with a Community Advisory Board (CAB) to explore how Communication Asset Mapping (CAM) could assist lay health advisors with the dissemination of evidence-based HC/RA information within AA faith communities. Methods: The research team and CAB conducted exploratory community-engaged group discussions with residents (n = 21) guided by Communication Infrastructure Theory, and used a community-engaged mapping process to inform the development of a CAM dissemination strategy. Results: Through textual analysis, the following conclusions were reached: (1) optimal locations (e.g., community centers) within specified neighborhood networks should have representatives who are trusted ambassadors to assist with HCRA information dissemination; (2) trusted community member voices should fully represent the neighborhood network in the community-engagement mapping process; (3) well-known and frequented geographic locations should provide a true representation of participants’ neighborhoods to create a robust health information network concerning HCRA. Conclusions: Community residents appreciated the engagement process; however, they felt that its impact was limited due to the lack of community voices within their neighborhoods to identify important communication resources within the network for optimal HCRA information dissemination. CAM, therefore, is an important public health strategy for the identification of trusted networks and useful communication resources within these networks. The strategy was also helpful in pinpointing people who could be critical communicators of emerging health information akin to HCRA. Full article

This research provides a comprehensive view of the geolocation of physical health assets in the city of Tarragona (Spain) and how these assets are used and recommended by healthcare professionals to promote healthy lifestyles. Focusing on the distribution and accessibility of sports facilities, such as outdoor gyms or football and basketball courts, this study highlights the importance of these assets in leading a healthy life and preventing chronic diseases. This article investigates the availability of these assets and their prescription by healthcare professionals to improve people’s quality of life through surveys and fieldwork. It evaluates both the knowledge healthcare professionals have about these available assets in the area and the types of physical activity they prescribe. The results show significant variability in the availability of physical health assets across different neighbourhoods. However, most residents have good walking access to these assets, especially in the central and western parts of the city. This study concludes that while physical health assets are an underutilised resource for healthcare professionals, enhancing the awareness and prescription of these assets could improve public health outcomes, particularly for older adults. Full article

Clients are increasingly looking for fast and effective means to quickly and frequently survey and communicate the condition of their buildings so that essential repairs and maintenance work can be done in a proactive and timely manner before it becomes too dangerous and expensive. Traditional methods for this type of work commonly comprise of engaging building surveyors to undertake a condition assessment which involves a lengthy site inspection to produce a systematic recording of the physical condition of the building elements, including cost estimates of immediate and projected long-term costs of renewal, repair and maintenance of the building. Current asset condition assessment procedures are extensively time consuming, laborious, and expensive and pose health and safety threats to surveyors, particularly at height and roof levels which are difficult to access. This paper aims at evaluating the application of convolutional neural networks (CNN) towards an automated detection and localisation of key building defects, e.g., mould, deterioration, and stain, from images. The proposed model is based on pre-trained CNN classifier of VGG-16 (later compaired with ResNet-50, and Inception models), with class activation mapping (CAM) for object localisation. The challenges and limitations of the model in real-life applications have been identified. The proposed model has proven to be robust and able to accurately detect and localise building defects. The approach is being developed with the potential to scale-up and further advance to support automated detection of defects and deterioration of buildings in real-time using mobile devices and drones. Full article