Social robots have been demonstrated to support neurodivergent individuals in health and educational settings, but the roles and benefits of social robots in the everyday lives of neurodivergent people are underexplored. We investigated daily-life use cases of robot dogs for neurodivergent individuals through three co-design workshops over five weeks. The workshops included interactions between neurodivergent participants and robot dogs, followed by feedback sessions. Participants showed high acceptance levels towards robot dogs and envisioned use cases that fulfilled practical, emotional, and social needs. Some participants associated robotic failures with rejection, leading us to further explore the impacts and communication of failures. Results showed how robot dogs can provide opportunities for users to be in a caregiving role and engage in interpersonal interactions. We conclude by discussing how to leverage the potential benefits of social robots by designing for social opportunities and ways to design failures to mitigate potential harms for users.

Securing employment and housing are key aspects of pursuing independent living. As these activities are increasingly practiced online, web accessibility of related services becomes critical for a successful major life transition. Support for this transition is especially important for people with autism or intellectual disability, who often face issues of underemployment and social isolation. In this study, we conducted semi-structured interviews and contextual inquiries with neurotypical adults and adults with autism or intellectual disability to understand common and unique goals, strategies, and challenges of neurodiverse adults when searching for employment and housing resources online. Our findings revealed that current interfaces adequately support practical (e.g., finance) goals but lack information on social (e.g., inclusivity) goals. Furthermore, unexpected search results and inaccessible social and contextual information diminished search experiences for neurodivergent users, which suggests the need for predictability and structured guidance in searching online. We conclude with design suggestions to make neurodivergent users’ online search experience an opportunity to demonstrate their independence.

OBJECTIVE: To create and evaluate a public health informatics tool, Florence, for communicating information to the public. MATERIALS AND METHODS: This user-centered design study included 3 phases: (1) an interview and survey study with public health practitioners to assess needs for creating infographics; (2) the application of assessment findings and public health-motivated design guidelines to the design and development of a public health-specific infographic design tool; and (3) a feasibility and usability study to evaluate the feasibility and usability of the tool. RESULTS: In phase 1, participants noted the importance of tailoring infographics to an audience and wanted flexible tools along with design guidance to help make fewer design decisions. In phase 2, we developed a prototype tool with: (1) layout and functionality familiar to PH users, (2) quick and intuitive ways to add and modify data in visualizations, and (3) health-focused visual elements. In phase 3, participants found Florence to be usable, providing an intuitive and straightforward experience, and that the focus on public health was useful. DISCUSSION: Based on needs assessments and existing literature, we created Florence along with public health practitioners to address their domain specific needs, ultimately leading to a tool that participants in our study deemed useful. Future research can build on our work to develop user-centered tools to meet their needs. CONCLUSION: Infographics are important for public health communication. Creating user-centered solutions to address the unique needs of public health can support communication efforts.

A conversational agent (CA) effectively facilitates online group discussions at scale. However, users may have expectations about how well the CA would perform that do not match with the actual performance, compromising technology acceptance. We built a facilitator CA that detects a member who has low contribution during a synchronous group chat discussion and asks the person to participate more. We designed three techniques to set end-user expectations about how accurately the CA identifies an under-contributing member: 1)information: explicitly communicating the accuracy of the detection algorithm, 2)explanation: providing an overview of the algorithm and the data used for the detection, and 3)adjustment: enabling users to gain a feeling of control over the algorithm. We conducted an online experiment with 163 crowdworkers in which each group completed a collaborative decision-making task and experienced one of the techniques. Through surveys and interviews, we found that the explanation technique was the most effective strategy overall as it reduced user embarrassment, increased the perceived intelligence of the CA, and helped users better understand the detection algorithm. In contrast, the information technique reduced members' contributions and the adjustment technique led to a more negative perceived discussion experience. We also discovered that the interactions with other team members diluted the effects of the techniques on users' performance expectations and acceptance of the CA. We discuss implications for better designing expectation-setting techniques for AI-team collaboration such as ways to improve collaborative decision outcomes and quality of contributions.

Conversational agents (CAs) can analyze online conversations using natural language techniques and effectively facilitate group discussions by sending supervisory messages. However, if a CA makes imperfect interventions, users may stop trusting the CA and discontinue using it. In this study, we demonstrate how inaccurate interventions of a CA and a conversational repair strategy can influence user acceptance of the CA, members' participation in the discussion, perceived discussion experience between the members, and group performance. We built a CA that encourages the participation of members with low contributions in an online chat discussion in which a small group (3-6 members) performs a decision-making task. Two types of errors can occur when detecting under-contributing members: 1) false-positive (FP) errors happen when the CA falsely identifies a member as under-contributing and 2) false-negative (FN) errors occur when the CA misses detecting an under-contributing member. We designed a conversational repair strategy that gives users a chance to contest the detection results and the agent sends a correctional message if an error is detected. Through an online study with 175 participants, we found that participants who received FN error messages reported higher acceptance of the CA and better discussion experience, but participated less compared to those who received FP error messages. The conversational repair strategy moderated the effect of errors such as improving the perceived discussion experience of participants who received FP error messages. Based on our findings, we offer design implications for which model should be selected by practitioners between high precision (i.e., fewer FP errors) and high recall (i.e., fewer FN errors) models depending on the desired effects. When frequent FP errors are expected, we suggest using the conversational repair strategy to improve the perceived discussion experience.

In online group discussions, balanced participation can improve the quality of discussion, members' satisfaction, and positive group dynamics. One approach to achieve balanced participation is to deploy a conversational agent (CA) that encourages participation of under-contributing members, and it is important to design communication strategies of the CA in a way that is supportive to the group. We implemented five communication strategies that a CA can use during a decision-making task in a small group synchronous chat discussion. The five strategies include messages sent to two types of recipients (@username vs. @everyone) crossed by two separate channels (public vs. private), and a peer-mediated strategy where the CA asks a peer to address the under-contributing member. Through an online study with 42 groups, we measured the balance of participation and perceptions about the CA by analyzing chat logs and survey responses. We found that the CA sending messages specifying an individual through a private channel is the most effective and preferred way to increase participation of under-contributing members. Participants also expressed that the peer-mediated strategy is a less intrusive and less embarrassing way of receiving the CA's messages compared to the conventional approach where the CA directly sends a message to the under-contributing member. Based on our findings, we discuss trade-offs of various communication strategies and explain design considerations for building an effective CA that adapts to different group dynamics and situations.

Traditional goal setting simply assumes a binary outcome for goal evaluation. This binary judgment does not consider a user’s effort, which may demotivate the user. This work explores the possibility of mitigating this negative impact with a slight modification on the goal evaluation criterion, by introducing a ‘margin’ that is widely used for quality control in the manufacturing fields. A margin represents a range near the goal where the user’s outcome will be regarded as ‘good enough’ even if the user fails to reach it. We explore users’ perceptions and behaviors through a large-scale survey study and a small-scale field experiment using a coaching system to promote physical activity. Our results provide positive evidence on the margin, such as lowering the burden of goal achievement and increasing motivation to make attempts. We discuss practical design implications on margin-enabled goal setting and evaluation for behavioral change support systems.

Social translucence theory argues that online collaboration systems should make contributors' activities visible to better achieve a common goal. Currently in medical crowdfunding sites, various non-monetary contributions integral to the success of a campaign, such as campaign promotions and offline support, are less visible than monetary contributions. Our work investigates ways to enrich social translucence in medical crowdfunding by aggregating and visualizing non-monetary contributions that reside outside of the current crowdfunding space. Three different styles of interactive visualizations were built and evaluated with medical crowdfunding beneficiaries and contributors. Our results reveal the perceived benefits and challenges of making the previously invisible non-monetary contributions visible using various design features in the visualizations. We discuss our findings based on the social translucence framework--visibility, awareness, and accountability--and suggest design guidelines for crowdfunding platform designers.

Effective communication between clinicians and parents of young children with developmental delays can decrease parents' anxiety, help them handle bad news, and improve their adherence to proposed interventions. However, parents have reported dissatisfaction regarding their current communication with clinicians, and they face cognitive and emotional challenges when discussing their child's developmental delays. In this paper, we present visualization as a facilitator of parent-clinician communication and how it could address existing communication challenges. Parents and clinicians anticipated visualization webtools would aid their communication by helping parents gain a better understanding of their child, acting as objective evidence, and highlighting the strength of the child as well as important medical concepts. In addition, visualization can act as a longitudinal record, helping parents track, explore, and share their child's developmental progress. Finally, we propose visualization as a tool to guide parents in their transition from feeling emotional and disempowered to advocating with confidence.

Visualizations are emerging as a means of spreading digital misinformation. Prior work has shown that visualization interpretation can be manipulated through slanted titles that favor only one side of the visual story, yet people still think the visualization is impartial. In this work, we study whether such effects continue to exist when titles and visualizations exhibit greater degrees of misalignment: titles whose message differs from the visually cued message in the visualization, and titles whose message contradicts the visualization. We found that although titles with a contradictory slant triggered more people to identify bias compared to titles with a miscued slant, visualizations were persistently perceived as impartial by the majority. Further, people's recall of the visualization's message more frequently aligned with the titles than the visualization. Based on these results, we discuss the potential of leveraging textual components to detect and combat visual-based misinformation with text-based slants.

It is often assumed that visual cues, which highlight specific parts of a visualization to guide the audience's attention, facilitate visualization storytelling and presentation. This assumption has not been systematically studied. We present an in-lab experiment and a Mechanical Turk study to examine the effects of integral and separable visual cues on the recall and comprehension of visualizations that are accompanied by audio narration. Eye-tracking data in the in-lab experiment confirm that cues helped the viewers focus on relevant parts of the visualization faster. We found that in general, visual cues did not have a significant effect on learning outcomes, but for specific cue techniques (e.g. glow) or specific chart types (e.g heatmap), cues significantly improved comprehension. Based on these results, we discuss how presenters might select visual cues depending on the role of the cues and the visualization type.

Slanted framing in news article titles induce bias and influence recall. While recent studies found that viewers focus extensively on titles when reading visualizations, the impact of titles in visualization remains underexplored. We study frames in visualization titles, and how the slanted framing of titles and the viewer's pre-existing attitude impact recall, perception of bias, and change of attitude. When asked to compose visualization titles, people used five existing news frames, an open-ended frame, and a statistics frame. We found that the slant of the title influenced the perceived main message of a visualization, with viewers deriving opposing messages from the same visualization. The results did not show any significant effect on attitude change. We highlight the danger of subtle statistics frames and viewers' unwarranted conviction of the neutrality of visualizations. Finally, we present a design implication for the generation of visualization titles and one for the viewing of titles.

Abstract Presenters, such as analysts briefing to an executive committee, often use visualizations to convey information. In these cases, providing clear visual guidance is important to communicate key concepts without confusion. This paper explores visual cues that guide attention to a particular area of a visualization. We developed a visual cue taxonomy distinguishing internal from external cues, designed a web tool based on the taxonomy, and conducted a user study with 24 participants to understand user preferences in choosing visual cues. Participants perceived internal cues (e.g., transparency, brightness, and magnification) as the most useful visual cues and often combined them with other internal or external cues to emphasize areas of focus for their audience. Interviews also revealed that the choice of visual cues depends on not only the chart type, but also the presentation setting, the audience, and the function cues are serving. Considering the complexity of choosing visual cues, we provide design implications for improving the organization, consistency, and integration of visual cues within existing workflows.

This paper presents a comparative study of two webtools developed to capture engagement via visualization of coordinated communication behavior in children with autism. A clear preference arose for different tasks based on behavior granularity emphasis in the two visualizations. The survey and interview results further revealed the importance of showing behavior patterns, rather than displaying a single behavior without context, in behavior visualization. Based on the results, we propose three granularity-related features to incorporate into behavioral visualizations for communication in clinical settings: separating modalities, coordinating dyadic interactions, and displaying micro-behaviors.

Joint attention is widely recognized as an important developmental milestone for children, and experts consider a lack of joint attention a defining characteristic of autism spectrum disorders (ASDs). While clinicians and researchers agree on the importance of joint attention, their definitions and methods for assessing joint attention vary. In this paper, we present the design process and the evaluation of EnGaze, a visualization-based Web tool for dyadic communicative behavior that highlights commonly discussed features of joint attention. While such visualization styles are not yet the norm in the clinical practices of behavioral and developmental psychology, we argue they should be and find that the introduction of these visual artifacts helped clinicians and researchers conceptualize their personal joint attention rules. Researchers envisioned a number of uses for EnGaze in their personal workflow, including identifying atypical communication patterns and providing a visual record for tracking behavior. The contributions of this paper are 1) an interactive visualization for exploring joint attention, 2) the documentation of an iterative design process for a clinical visualization tool, 3) illustrations of EnGaze use cases with active practitioners in the behavioral sciences, and (4) the discussions surrounding the implications of introducing such visualizations in behavioral science communities.

Traditional medical fundraising charities have been relying on third-party watchdogs and carefully crafting their reputation over time to signal their credibility to potential donors. As medical fundraising campaigns migrate to online platforms in the form of crowdfunding, potential donors can no longer rely on the organization's traditional methods for achieving credibility. Individual fundraisers must establish credibility on their own. Potential donors, therefore, seek new factors to assess the credibility of crowdfunding campaigns. In this paper, we investigate current practices in assessing the credibility of online medical crowdfunding campaigns. We report results from a mixed-methods study that analyzed data from social media and semi-structured interviews. We discovered eleven factors associated with the perceived credibility of medical crowdfunding. Of these, three communicative/emotional factors were unique to medical crowdfunding. We also found a distinctive validation practice, the collective endorsement. Close-connections' online presence and external online communities come together to form this collective endorsement in online medical fundraising campaigns. We conclude by describing how fundraisers can leverage collective endorsements to improve their campaigns' perceived credibility.