With point-of-care (POC) diagnostic devices becoming increasingly available to untrained users, it will be critical to understand how real-world user behavior can best inform and guide the engineering design process. Social sciences present frameworks for analyzing user behavior, but they have not yet been applied to POC diagnostics in a methodical manner. Here, we develop a framework that synthesizes two models that can collectively account for user behavior and experience with POC diagnostic devices: a social psychological information-motivation-behavior (IMB) model (first described by Fisher and Fisher) for identifying determinants for health-related behavior, and user experience (UX) elements for studying interactions between users and products. Based on studies of 40 naïve users of our smartphone-enabled microfluidics device that can be used for HIV home-testing, we found that untrained participants could perform 90% of steps correctly, with engineering design elements that provided feedback that was either direct (e.g., a light or click) or binary (e.g., a switch) enhancing usability. Interestingly, of the steps performed incorrectly, over 70% were due not to errors in the device or user operation, but user-to-user variability (e.g. time in collecting fingerstick and force applied to initiate vacuum), which could be addressed by further modifications to the device. Overall, this study suggests that microfluidic POC HIV home-testing is likely to benefit from smartphone integration, and that engineering design of POC diagnostic devices can benefit from a structured evaluation of user behavior and experience, as guided by a social-psychological framework, which emphasizes user credibility, accessibility, acceptability, usability, and value.
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http://dx.doi.org/10.1039/c9lc00188c | DOI Listing |
Sci Rep
December 2024
The Department of Mechanical Engineering and Mechatronics, Ariel University, Ariel, Israel.
Autism spectrum disorder (ASD) involves challenges in communication and social interaction, including challenges in recognizing emotions. Existing technological solutions aim to improve social behaviors in individuals with ASD by providing learning aids. This paper presents a real-time environmental translator designed to enhance social behaviors in individuals with ASD using sensory substitution.
View Article and Find Full Text PDFImplement Sci Commun
December 2024
Department of Health Promotion and Behavioral Sciences, School of Public Health, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Houston, TX, 77030, USA.
Background: All for Them is a theory-based and evidence-informed multilevel, multicomponent program delivered through schools to increase HPV vaccination among medically underserved youth across Texas. Given the potential logistical challenges of program implementation, understanding how to best support the implementation and sustainment of the program is critical. The overall goals of this study are twofold: 1) develop a multifaceted implementation strategy, Implementing All for Them (IM-AFT); and 2) evaluate the impact of IM-AFT on implementation outcomes for schools and healthcare providers to successfully implement All for Them in their respective settings.
View Article and Find Full Text PDFSci Rep
December 2024
College of Furnishings and Industrial Design, Nanjing Forestry University, No.159 Longpan Road, Nanjing, 210037, Jiangsu, China.
The widespread use of mobile applications (apps) offers a new platform for sustaining traditional culture, yet insufficient focus on interface design has hindered user experience. This paper focuses on traditional Chinese medicine (TCM) apps, examining user preferences for interface design elements and their combinations across four dimensions: visual effects, functional attributes, layout, and interaction modes. Utilizing Conjoint Analysis Method (CAM), this study quantitatively explores user preferences for the combination schemes of 18 orthogonal designs.
View Article and Find Full Text PDFNeural Netw
December 2024
School of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China. Electronic address:
Tag-aware recommender systems leverage the vast amount of available tag records to depict user profiles and item attributes precisely. Recently, many researchers have made efforts to improve the performance of tag-aware recommender systems by using deep neural networks. However, these approaches still have two key limitations that influence their ability to achieve more satisfactory results.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu, China.
Background: Large language models (LLMs) are increasingly integrated into medical education, with transformative potential for learning and assessment. However, their performance across diverse medical exams globally has remained underexplored.
Objective: This study aims to introduce MedExamLLM, a comprehensive platform designed to systematically evaluate the performance of LLMs on medical exams worldwide.
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