50,762 research outputs found
Towards a Holistic Approach to Designing Theory-based Mobile Health Interventions
Increasing evidence has shown that theory-based health behavior change
interventions are more effective than non-theory-based ones. However, only a
few segments of relevant studies were theory-based, especially the studies
conducted by non-psychology researchers. On the other hand, many mobile health
interventions, even those based on the behavioral theories, may still fail in
the absence of a user-centered design process. The gap between behavioral
theories and user-centered design increases the difficulty of designing and
implementing mobile health interventions. To bridge this gap, we propose a
holistic approach to designing theory-based mobile health interventions built
on the existing theories and frameworks of three categories: (1) behavioral
theories (e.g., the Social Cognitive Theory, the Theory of Planned Behavior,
and the Health Action Process Approach), (2) the technological models and
frameworks (e.g., the Behavior Change Techniques, the Persuasive System Design
and Behavior Change Support System, and the Just-in-Time Adaptive
Interventions), and (3) the user-centered systematic approaches (e.g., the
CeHRes Roadmap, the Wendel's Approach, and the IDEAS Model). This holistic
approach provides researchers a lens to see the whole picture for developing
mobile health interventions
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Sensory semantic user interfaces (SenSUI)
Rapid evolution of the World Wide Web with its underlying sources of data, knowledge, services and applications continually attempts to support a variety of users, with different backgrounds, requirements and capabilities. In such an environment, it is highly unlikely that a single user interface will prevail and be able to fulfill the requirements of each user adequately. Adaptive user interfaces are able to adapt information and application functionalities to the user context. In contrast, pervasive computing and sensor networks open new opportunities for context aware platforms, one that is able to improve user interface adaptation reacting to environmental and user sensors. Semantic web technologies and ontologies are able to capture sensor data and provide contextual information about the user, their actions, required applications and environment. This paper investigates the viability of an approach where semantic web technologies are used to maximize the efficacy of interface adaptation through the use of available ontology
User-centred design of flexible hypermedia for a mobile guide: Reflections on the hyperaudio experience
A user-centred design approach involves end-users from the very beginning. Considering users at the early stages compels designers to think in terms of utility and usability and helps develop the system on what is actually needed. This paper discusses the case of HyperAudio, a context-sensitive adaptive and mobile guide to museums developed in the late 90s. User requirements were collected via a survey to understand visitors’ profiles and visit styles in Natural Science museums. The knowledge acquired supported the specification of system requirements, helping defining user model, data structure and adaptive behaviour of the system. User requirements guided the design decisions on what could be implemented by using simple adaptable triggers and what instead needed more sophisticated adaptive techniques, a fundamental choice when all the computation must be done on a PDA. Graphical and interactive environments for developing and testing complex adaptive systems are discussed as a further
step towards an iterative design that considers the user interaction a central point. The paper discusses
how such an environment allows designers and developers to experiment with different system’s behaviours and to widely test it under realistic conditions by simulation of the actual context evolving over time. The understanding gained in HyperAudio is then considered in the perspective of the
developments that followed that first experience: our findings seem still valid despite the passed time
ReCon: Revealing and Controlling PII Leaks in Mobile Network Traffic
It is well known that apps running on mobile devices extensively track and
leak users' personally identifiable information (PII); however, these users
have little visibility into PII leaked through the network traffic generated by
their devices, and have poor control over how, when and where that traffic is
sent and handled by third parties. In this paper, we present the design,
implementation, and evaluation of ReCon: a cross-platform system that reveals
PII leaks and gives users control over them without requiring any special
privileges or custom OSes. ReCon leverages machine learning to reveal potential
PII leaks by inspecting network traffic, and provides a visualization tool to
empower users with the ability to control these leaks via blocking or
substitution of PII. We evaluate ReCon's effectiveness with measurements from
controlled experiments using leaks from the 100 most popular iOS, Android, and
Windows Phone apps, and via an IRB-approved user study with 92 participants. We
show that ReCon is accurate, efficient, and identifies a wider range of PII
than previous approaches.Comment: Please use MobiSys version when referencing this work:
http://dl.acm.org/citation.cfm?id=2906392. 18 pages, recon.meddle.mob
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