Adapting health-risk communication to the specific cultural contexts of diverse populations : an assessment of malaria-treatment programs in Liberia

Drawing on theories of technical communication, rhetoric, literacy, language and culture, and medical anthropology, this dissertation explores how local culture and traditions can be incorporated into health-risk-communication-program design and implementation, including the design and dissemination of health-risk messages. In a modern world with increasing global economic partnerships, mounting health and environmental risks, and cross-cultural collaborations, those who interact with people of different cultures have “a moral obligation to take those cultures seriously, including their social organization and values” (Hahn and Inhorn 10). Paradoxically, at the same time as we must carefully adapt health, safety, and environmental-risk messages to diverse cultures and populations, we must also recognize the increasing extent to which we are all becoming part of one, vast, interrelated global village. This, too, has a significant impact on the ways in which healthcare plans should be designed, communicated, and implemented. Because communicating across diverse cultures requires a system for “bridging the gap between individual differences and negotiating individual realities” (Kim and Gudykunst 50), both administrators and beneficiaries of malaria-treatment-and-control programs (MTCPs) in Liberia were targeted to participate in this study. A total of 105 people participated in this study: 21 MTCP administrators (including designers and implementers) completed survey questionnaires on program design, implementation, and outcomes; and 84 MTCP beneficiaries (e.g., traditional leaders and young adults) were interviewed about their knowledge of malaria and methods for communicating health risks in their tribe or culture. All participants showed a tremendous sense of courage, commitment, resilience, and pragmatism, especially in light of the fact that many of them live and work under dire socioeconomic conditions (e.g., no electricity and poor communication networks). Although many MTCP beneficiaries interviewed for this study had bed nets in their homes, a majority (46.34 percent) used a combination of traditional herbal medicine and Western medicine to treat malaria. MTCP administrators who participated in this study rated the impacts of their programs on reducing malaria in Liberia as moderately successful (61.90 percent) or greatly successful (38.10 percent), and they offered a variety of insights on what they might do differently in the future to incorporate local culture and traditions into program design and implementation. Participating MTCP administrators and beneficiaries differed in their understanding of what “cultural incorporation” meant, but they agreed that using local indigenous languages to communicate health-risk messages was essential for effective health-risk communication. They also suggested that understanding the literacy practices and linguistic cultures of the local people is essential to communicating health risks across diverse cultures and populations.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.