Advancing the Strategic Messages Affecting Robot Trust Effect: The Dynamic of User- and Robot-Generated Content on Human-Robot Trust and Interaction Outcomes.

Human-robot interaction (HRI) will soon transform and shift the communication landscape such that people exchange messages with robots. However, successful HRI requires people to trust robots, and, in turn, the trust affects the interaction. Although prior research has examined the determinants of human-robot trust (HRT) during HRI, no research has examined the messages that people received before interacting with robots and their effect on HRT. We conceptualize these messages as SMART (Strategic Messages Affecting Robot Trust). Moreover, we posit that SMART can ultimately affect actual HRI outcomes (i.e., robot evaluations, robot credibility, participant mood) by affording the persuasive influences from user-generated content (UGC) on participatory Web sites. In Study 1, participants were assigned to one of two conditions (UGC/control) in an original experiment of HRT. Compared with the control (descriptive information only), results showed that UGC moderated the correlation between HRT and interaction outcomes in a positive direction (average Δr = +0.39) for robots as media and robots as tools. In Study 2, we explored the effect of robot-generated content but did not find similar moderation effects. These findings point to an important empirical potential to employ SMART in future robot deployment.

The Role of Reciprocity in Verbally Persuasive Robots.

The current research examines the persuasive effects of reciprocity in the context of human-robot interaction. This is an important theoretical and practical extension of persuasive robotics by testing (1) if robots can utilize verbal requests and (2) if robots can utilize persuasive mechanisms (e.g., reciprocity) to gain human compliance. Participants played a trivia game with a robot teammate. The ostensibly autonomous robot helped (or failed to help) the participants by providing the correct (vs. incorrect) trivia answers. Then, the robot directly asked participants to complete a 15-minute task for pattern recognition. Compared to no help, results showed that a robot's prior helping behavior significantly increased the likelihood of compliance (60 percent vs. 33 percent). Interestingly, participants' evaluations toward the robot (i.e., competence, warmth, and trustworthiness) did not predict compliance. These results also provided an insightful comparison showing that participants complied at similar rates with the robot and with computer agents. This result documents a clear empirically powerful potential for the role of verbal messages in persuasive robotics.

An Effort to Increase Organ Donor Registration Through Intergroup Competition and Electronic Word of Mouth.

The effort to increase Web organ donation registrations in Michigan by enhancing 2 types of university campaigns with social media strategies informed by social identity theory is the focus of this research. The two campaigns focused on either ingroup or rivalry outgroup social identification, and each was enhanced with individually focused social media in the first year of the campaign and with electronic word of mouth in Year 2 of the campaign. Results indicated that individually focused social media such as Facebook ads worked well in rivalry campaigns (in which registrations increased two times over baseline) but not in ingroup identification campaigns (in which registrations decreased significantly over baseline when ads were introduced in the first year of each type of campaign). Electronic word-of-mouth strategies worked well in both ingroup identification campaigns (in which registrations increased two times over baseline) and rivalry campaigns (in which registrations rose almost eight times over baseline, when strategies were introduced in the second year of each type of campaign).

Reciprocity in computer-human interaction: source-based, norm-based, and affect-based explanations.

Individuals often apply social rules when they interact with computers, and this is known as the Computers Are Social Actors (CASA) effect. Following previous work, one approach to understand the mechanism responsible for CASA is to utilize computer agents and have the agents attempt to gain human compliance (e.g., completing a pattern recognition task). The current study focuses on three key factors frequently cited to influence traditional notions of compliance: evaluations toward the source (competence and warmth), normative influence (reciprocity), and affective influence (mood). Structural equation modeling assessed the effects of these factors on human compliance with computer request. The final model shows that norm-based influence (reciprocity) increased the likelihood of compliance, while evaluations toward the computer agent did not significantly influence compliance.

Osteopathic medical student learning competency.

BACKGROUND AND OBJECTIVES: The purpose of this paper is to report on the development and implementation of a learning competency assessment survey for first-year medical students. We began by defining learning competencies in a manner that is parallel to the clinical competencies resulting in a self-assessment survey of 1,998 first-year osteopathic medical students from 25 osteopathic medical schools. Results from the online survey indicated that the internal structure of the instrument and the reliability of the items were strong. The survey revealed that first-year medical students were most confident in their ability to perform in a professional manner and least confident in their ability to manage their curriculum, particularly with the assistance of faculty and advisors. A regression analysis indicated that the best predictors of curricular involvement were Student Learning and Improvement, Knowledge of Osteopathic Philosophy and Skills, Interpersonal Communication, and Systems Knowledge. However, Medical Knowledge and Professionalism did not provide any unique variance to the model, suggesting that students' confidence in their undergraduate science training or self perceptions of their professionalism had little to do with their confidence in navigating medical school.