Human-Computer Interaction in Health and Wellness: Research and Publication Opportunities

In this introduction, we address three distinct aspects of the special issue topic “human-computer interaction (HCI) in health and wellness”. First, we assess the trajectory of HCI research in health topics in top HCI journals during the 1995-2012 period. We then contrast this overall publication trajectory with the health sector component of gross domestic product (GDP)—applied as a proxy measure of social need—across seven countries that are top producers of HCI research. Second, we describe how one can use the human-technology innovation framework to understand the range of settings in which HCI research in health topics can be conducted. Grounded in this framework, we propose a structure to categorize health related HCI publication and to identify gaps in this research. Third, we apply the proposed structure to categorize and introduce five papers chosen to represent the special issue topic

User Experience-driven Innovation—Theory and Practice: Introduction to Special Issue

This special issue is motivated by the need for user experience (UX) innovation ecosystems and the difficulty of creating and maintaining them. The papers in this special issue reflect the emerging views of the scholars and industry experts involved in one such UX innovation ecosystem. Authors presented the papers at the 2019 UX Symposium (https://uxsym.org/), an annual conference with the mission to continue to build its vibrant community of scholars and practitioners dedicated to advancing UX theory, education, and practice

Using Audio Augmented Reality to Support Decision Making

Audio augmented reality (AR) is becoming increasingly popular as a medium for communicating additional layers of information about a user’s environment. This extended abstract reports the preliminary results of a study examining the impact of an audio AR enabled mobile decision aid, FoodGlance, on users’ decision quality as well as their overall experience of the decision-making process. Research shows that people often find nutrition facts labels confusing and difficult to use [1]. FoodGlance was designed to make it easier for people to choose healthy products based on their dietary needs and preferences. FoodGlance uses OCR technology to extract textual information from nutrition fact labels and then translates it into simple feedback [2]. In this study, the feedback was provided in three different ways: audio AR, visual, and the combination of the two. Audio AR was provided via Bose glasses. Visual feedback, consistent with our previous study, was displayed as a pop-up on the smartphone showing thumbs up (good amount) or thumps down (bad amount) for sugar, fat, and protein separately [2]. For this study we used the FDA’s 5-20 percent daily value rule to design feedback. The feedback engine in FoodGlance, however, is not limited to this rule and can be modified by users

Moods and Their Relevance to Systems Usage Models within Organizations: An Extended Framework

Traditionally, information systems (IS) usage models have examined user behavior within a cognitive framework, that is, these models suggest that a user’s cognition influences his/her IS usage behavior. Research over the past three decades has shown that mood, one’s global feeling state at a given time, can significantly impact a person’s cognitive processes. Mood effects on cognition are particularly relevant to organizational settings. Because moods are pervasive, they provide a stable context for cognitive processes that influence behavior at work; therefore, the inclusion of mood in individual IS usage models that support organizational tasks is both relevant and necessary. Because positive mood can enhance performance under certain circumstances, mood management is also relevant to IS usage models. Thus, we highlight how moods can be managed via IS and propose a model that takes into account users’ moods at the time they work with a system. This model provides an extended framework for incorporating relevant mood literature into current IS usage behavioral models. With this model, researchers can examine certain aspects of the model (such as how IS design can influence user feeling states or how users’ moods can impact their behavior), or conduct more comprehensive research using the entire model. This model can contribute to theory by providing a more complete picture of user behavior, and contribute to practice by helping mangers plan for desired outcomes

The effect of positive mood on intention to use computerized decision aids

While psychology research indicates that positive mood enhances cognition and behavior, MIS researchers have largely ignored the potential effects of positive mood on user acceptance of new information technologies (IT). Using two cognitive theories about mood and memory, positive mood theory and the affect infusion model (AIM), this study develops hypotheses about users’ acceptance of new IT under two mood conditions and two levels of uncertainty. These hypotheses are investigated via a lab experiment using a computerized decision aid. The lab experiment found that positive mood increased acceptance, as compared to a control group, under both levels of uncertainty. These results held for both induced and naturally occurring positive mood. The results for the high uncertainty condition along with results of two post-hoc tests are consistent with positive mood theory, but not with the AIM. These results indicate that mood is an important focus for future MIS acceptance research, which should be based on positive mood theory rather than the AIM