Songwriting has long served as a powerful medium for expressing unconscious emotions and fostering self-awareness in psychotherapy. Due to the auditory-centric nature of traditional approaches, Deaf and Hard-of-Hearing (DHH) individuals have often been excluded from music’s therapeutic benefits. In response, this study presents a music psychotherapy tool co-designed with therapists, integrating conversational agents (CAs) and music generative AI as symbolic and therapeutic media. Through a usage study with 23 DHH individuals, we found that collaborative songwriting with the CA enabled them to experience emotional release, reinterpretation, and deeper self-understanding. In particular, the CA’s strategies—supportive empathy, example response options, and visual-based metaphors—were found to facilitate musical dialogue effectively for DHH individuals. These findings contribute to inclusive AI design by showing the potential of human–AI collaboration to bridge therapeutic and artistic practices.

The rapid advancement of generative AI (GenAI) is expanding access to songwriting, offering a new medium of self-expression for Deaf and Hard-of-Hearing (DHH) individuals. However, emerging technologies that support DHH individuals in expressing themselves through music have largely been evaluated in single-session settings and often fall short in helping users unfamiliar with songwriting convey personal narratives or sustain engagement over time. This paper explores songwriting as an extended, music-based journaling practice that supports sustained emotional reflection over multiple sessions. We introduce SoulNote, a GenAI system enabling DHH to engage in iterative songwriting. Grounded in user-centered design, including a design workshop, a preliminary study, and a multi-session diary study, our findings show that ongoing songwriting with SoulNote facilitated emotional growth across three dimensions: self-insight, emotion regulation, and everyday attitudes toward emotions and self-care. Overall, this work demonstrates how GenAI can support marginalized communities by transforming creative expression into a daily practice of self-discovery and reflection.

Professional self-representation involves constructing identities that reflect personal values while aligning with the norms of professional communities. Many people turn to generative AI for help, but misalignments between LLM outputs and self-understanding hinder authenticity and accuracy of the content. To explore how LLMs can support co-creation aligned, authentic self-representational content, we designed LL.me, a web-based probe based on bi-directional alignment that utilizes users’ resumes and guides them through iterative cycles of refining AI-generated self-representations. Our user study with 14 participants showed users engaged in identity work with the tool, re-framing content to emphasize their personal values, imparting tacit knowledge from their communities of practice, and leveraging system explainability features as a proxy for how the representation would be perceived by others. We demonstrate how LLM-based tools can facilitate a co-constructive process of identity formation, helping individuals actively shape their professional self-representations in collaboration with the AI.

While family informatics has been developed for monitoring and tracking family-centered health data, there remains a gap in understanding how family informatics can support families in reflecting on their social behaviors and emotional dynamics. We address this gap with SELaD, a system that captures and visualizes social-emotional data from daily family interactions using audio, video, and physiological sensors. In a semi-naturalistic study with 17 families (n = 51), we investigated how this data facilitates reflection. Our findings reveal a process we term relational reflection, where families collaboratively interpret multimodal data to deepen their understanding of conversational dynamics and emotional influences by recalling their shared history and expectation of good communication. This process was particularly enriched by emotional data from multiple sources that families could cross-reference and reconcile. This work presents SELaD as a technology probe and empirically grounds the concept of relational reflection, positioning it as a foundation for designing future reflective technologies.

Large Language Models are often trained on data reflecting neurotypical norms, yet are increasingly deployed to support neurodivergent users in sensitive domains like job-seeking.We examine interactions between neurodivergent job-seekers and a GPT-4powered career support chatbot through the lens of misalignment.Through analysis of over 300 chat logs and interviews with 15 neurodivergent participants, we found that the chatbot frequently misrepresented users' skills, imposed neurotypical language and expectations, and provided generic or inappropriate advice-even when relevant user data was available.Participants expected the chatbot to interpret implicit insights from their data, however, they sometimes lacked the clarity or confidence to correct the system when it did not, revealing gaps in both AI design and user understanding of system function.Our findings underscore the need for bi-directional alignment between neurodivergent users and LLMs, and call for design strategies that integrate neurodivergent perspectives and preferences to ensure more authentic, personalized, and human-centered AI support.

In remote psychotherapy, challenges arising from remote client-therapist interactions can impact the therapeutic alliance and overall outcomes. HCI research has focused on leveraging sensing technology to bridge gaps in remote interactions. In this work, we investigate the values and risks of integrating sensing technology in remote psychotherapy, specifically to capture and interpret non-verbal cues, by conducting a speculative design study with both clients and therapists. Our findings reveal that sensing technology has the potential to facilitate self-reflection in therapy. The sharing of tracked non-verbal cues could also possibly foster mutual disclosure, supporting therapists' judgments and balancing power dynamics between clients and therapists. However, clients and therapists were concerned about the accuracy of sensing systems, potential privacy threats, and additional cognition burden. Our insights into system values imply how sensing technology could potentially balance power dynamics in client-therapist relationships as well as general interpersonal relationships. We also emphasize the increased considerations in sensing-technology-empowered communication for remote psychotherapy than in non-vulnerable settings.

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.

Supported employment programs have demonstrated the ability to enhance employment outcomes for neurodivergent individuals by offering personalized job coaching that aligns with the strengths of each individual. While various technological interventions have been designed to support these programs, technologies that hyperfocus on users’ assumed challenges through deficit-based design have been criticized due to their potential to undermine the agency of neurodivergent individuals. Therefore, we use strengths-based co-design to explore the opportunities for a technology that supports neurodivergent employees using their strengths. The co-design activities uncovered our participants’ current strategies to address workplace challenges, the strengths they employ, and the technology designs that our participants developed to operationalize those strengths in a supportive technology. We find that incorporating strengths-based strategies for emotional regulation, interpersonal problem solving, and learning job-related skills can provide a supportive technology experience that bolsters neurodiverse employees’ agency and independence in the workplace. In response, we suggest design implications for using neurodiverse strengths as design requirements and how to design for independence in workplace.

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.

Early detection and intervention for relapse is important in the treatment of schizophrenia spectrum disorders. Researchers have developed AI models to predict relapse from patient-contributed data like social media. However, these models face challenges, including misalignment with practice and ethical issues related to transparency, accountability, and potential harm. Furthermore, how patients who have recovered from schizophrenia view these AI models has been underexplored. To address this gap, we first conducted semi-structured interviews with 28 patients and reflexive thematic analysis, which revealed a disconnect between AI predictions and patient experience, and the importance of the social aspect of relapse detection. In response, we developed a prototype that used patients' Facebook data to predict relapse. Feedback from seven patients highlighted the potential for AI to foster collaboration between patients and their support systems, and to encourage self-reflection. Our work provides insights into human-AI interaction and suggests ways to empower people with schizophrenia.

Co-design of technology encourages participation and decision-making input of end-users. In the case of technologies for individuals with Intellectual and Developmental Disabilities (IDD), the end-users are historically left out of the design process. Further deepening the disconnect between this group and technology, they are also excluded from formal technology design knowledge sharing, such as college courses. To address this, our study investigates the efficacy of a formal classroom adaptation of co-design activities to encourage learning and participation. Through collaboration between educators and designers, we adopted user-centered co-design activities to facilitate knowledge and application of technological design methods within a class of 13 students with IDD. Findings uncovered factors contributing to co-teaching collaboration planning and reflection between educators and designers, and ways that activities can provide accessible collaborative learning environments for students with IDD by supporting collaboration, cognitive engagement, and meta-cognition. We discuss how these factors can support successful co-teacher collaborations that promote student empowerment. Finally, we contribute collaborative co-teaching strategies for educational co-design activities for individuals with IDD.

Inclusive workplaces require mutual efforts between neurotypical (NT) and neurodivergent (ND) employees to understand one another’s viewpoints and experiences. Currently, the majority of inclusivity training places the burden of change on NDs to conform to NT social-behavioral standards. Our research examines moving toward a more equal effort distribution by exploring virtual reality (VR) design opportunities to build NTs’ understanding of ND workplace experiences. Using participatory design, including generative toolkits and design meetings, we surfaced two main themes that could bridge gaps in understanding: (1) NTs’ recognition of NDs’ strengths and efforts at work, and (2) NTs’ understanding of NDs’ differences. We present a strengths-based assessment of ND traits in the workplace, focusing on how workplaces can support NDs’ success. Finally, we propose VR simulation designs that communicate these themes to represent ND experiences, emphasizing their strengths and viewpoints so that NT co-workers can better empathize and accommodate them.

Virtual reality (VR) has become a valuable tool for social and educational purposes for autistic people, as it provides flexible environmental support to create a variety of experiences. A growing body of recent research has examined the behaviors of autistic people using sensor-based data to better understand autistic people and investigate the effectiveness of VR. Comprehensive analysis of the various signals that can be easily collected in the VR environment can promote understanding of autistic people. While this quantitative evidence has the potential to help both autistic people and others (e.g., autism experts) to understand behaviors of autistic people, existing studies have focused on single signal analysis and have not determined the acceptability of signal analysis results from the autistic person’s point of view. To facilitate the use of multiple sensor signals in VR for autistic people and experts, we introduce V-DAT (Virtual Reality Data Analysis Tool), designed to support a VR sensor data handling pipeline. V-DAT takes into account four sensor modalities—head position and rotation, eye movement, audio, and physiological signals—that are actively used in current VR research for autistic people. We explain the characteristics and processing methods of the data for each modality as well as the analysis with comprehensive visualizations of V-DAT. We also conduct a case study to investigate the feasibility of V-DAT as a way of broadening understanding of autistic people from the perspectives of both autistic people and autism experts. Finally, we discuss issues with the process of V-DAT development and complementary measures for the applicability and scalability of a sensor data management system for autistic people.

Transition planning is a collaborative process to promote agency in students with disabilities by encouraging them to participate in setting their own goals with team members and learn ways to assess their progress towards the goals. For autistic young adults who experience a lower employment rate, less stability in employment, and lower community connections than those with other disabilities, successful transition planning is an important opportunity to develop agency towards preparing and attaining success in employment and other areas meaningful to them. However, a failure of consistent information sharing among team members and opportunities for agency in students has prevented successful transition planning for autistic students. Therefore, this work brings causal agency theory and the collaborative reflection framework together to uncover ways transition teams can develop students' agency by collaboratively reflecting on students' inputs related to transition goals and progress. By interviewing autistic students, parents of autistic students, and professionals who were involved in transition planning, we uncovered that teams can better support student agency by accommodating their needs and encouraging their input in annual meetings, building relationships through transparent and frequent communication about day-to-day activities, centering goals on student's interests, and supporting student's skill-building in areas related to their transition goals. However, we found that many teams were not enacting these practices, leading to frustration and negative outcomes for young adults. Based on our findings, we propose a role for autistic students in the collaborative reflection framework that encouraged participation and builds causal agency. We also make design recommendations to encourage autistic students' participation in collaborative reflection around long-term and short-term needs in ways that promote their causal agency.

While birth control pills are one of the most common forms of contraception, their usage has several emotional and physical costs, such as taking the pill daily and experiencing hormonal side effects. The burden of these tasks in relationships generally falls on the pill user with minimal involvement from their partner. In this study, we conducted semi-structured interviews with pill users and their partners to investigate the differences between their perceived current and ideal divisions of birth control responsibility. During the interview, we presented a collaborative birth control tracking app prototype to examine how such technology can overcome these discrepancies. We found that pill users were unsatisfied with their partners' engagement in contraceptive tasks but did not communicate this well. Meanwhile, partners wanted to contribute more to pregnancy prevention but did not know how. When presented with our app prototype, users and partners stated that our design could address these issues by improving communication between users and partners. In particular, users appreciated how technology could increase engagement and support from their partner, and partners liked that our app presented several concrete ways to become more involved and show emotional support. However, privacy issues exist given the sensitive nature of contraception. We highlight design considerations that should be kept in mind about privacy while recognizing pill users' efforts and promoting partners' involvement.

Contact tracers assist in containing the spread of highly infectious diseases such as COVID-19 by engaging community members who receive a positive test result in order to identify close contacts. Many contact tracers rely on community member’s recall for those identifications, and face limitations such as unreliable memory. To investigate how technology can alleviate this challenge, we developed a visualization tool using de-identified location data sensed from campus WiFi and provided it to contact tracers during mock contact tracing calls. While the visualization allowed contact tracers to find and address inconsistencies due to gaps in community member’s memory, it also introduced inconsistencies such as false-positive and false-negative reports due to imperfect data, and information sharing hesitancy. We suggest design implications for technologies that can better highlight and inform contact tracers of potential areas of inconsistencies, and further present discussion on using imperfect data in decision making.

Pervasive symptoms of people with autism spectrum disorder (ASD), such as a lack of social and communication skills, are major challenges to be embraced in the workplace. Although much research has proposed VR training programs, their effectiveness is somewhat unclear, since they provide limited, one-sided interactions through fixed scenarios or do not sufficiently reflect the characteristics of people with ASD (e.g., preference for predictable interfaces, sensory issues). In this paper, we present VISTA, a VR-based interactive social skill training system for people with ASD. We ran a user study with 10 people with ASD and 10 neurotypical people to evaluate user experience in VR training and to examine the characteristics of people with ASD based on their physical responses generated by sensor data. The results showed that ASD participants were highly engaged with VISTA and improved self-efficacy after experiencing VISTA. The two groups showed significant differences in sensor signals as the task complexity increased, which demonstrates the importance of considering task complexity in eliciting the characteristics of people with ASD in VR training. Our findings not only extend findings (e.g., low ROI ratio, EDA increase) in previous studies but also provide new insights (e.g., high utterance rate, large variation of pupil diameter), broadening our quantitative understanding of people with ASD.

A sense of community is important in encouraging people to contribute to a variety of causes and the communities that support them. Researchers have identified website design features that can engender a sense of community on sites to promote contributions. However, most findings about design features are based on observational empirical research testing single features at a time or on standard practice and rarely use integrated theories to provide rationale for their design suggestions. This work investigates ways to re-design an entire website---with a simulated medical crowdfunding interface entitled Community Journey---informed by Sense of Community Theory to increase site visitors' sense of community and contributions. A between-subjects experiment revealed that the Community Journey interface increased potential supporters' sense of community and their overall willingness to contribute via monetary donations, campaign shares, personal messages, and offline support. Think-aloud interviews identified the interface features responsible for the overall increase in willingness to contribute. Finally, we suggest theory driven design implications for creating websites to build a strong support community and to encourage various contributions.

A growing number of organizations are hiring autistic individuals as they start to recognize the value of a neurodiverse workforce. Despite this trend, the lack of support for autistic employees in workplaces complicates their employment. However, little is known about how people around autistic individuals can support them to create pleasant employment experiences. In this work, we develop the concept of the Workplace Playbook VR to investigate how virtual reality (VR) can help autistic people develop their work-related social communication skills in partnership with people in their support network. Using a video prototype to present the concept, we interviewed 28 participants, including 10 autistic people and 18 members of their support networks, which included family members and professionals. Our interviews revealed that the Workplace Playbook VR program can provide common ground for autistic people and members of their support network to participate in more empathetic communication regarding workplace challenges. Despite the benefits, we identified the potential misuse of social communication skills training features of the VR program to correct the personal characteristics of autistic individuals. Furthermore, to cultivate inclusive workplace environments, we found the needs of VR development not only for autistic people but also for neurotypical employees to promote their understanding of autism and empathy toward autistic employees. We suggest VR designs that promote a sense of agency and self-advocacy for autistic employees, and autism awareness and acceptance training for neurotypical employees.

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.

People desire to present themselves favorably to others. However, medical crowdfunding beneficiaries are often expected to present their dire medical conditions and financial straits to solicit financial support. To investigate how beneficiaries convey their situation on medical crowdfunding pages and how contributors perceive the presented information, we interviewed both medical crowdfunding beneficiaries and contributors. While beneficiaries emphasized the serious of their medical situations to signal their deservedness of support, contributor participants gave less attention to that content. Rather, they focused on their impression of the beneficiary's character formed by various features of contributions such as the contributor's names, messages, and shared pictures. These contribution features further signaled common connections between the beneficiary and contributors and each contributor's unique involvement in the beneficiary's medical journey. However, the contribution amount resulted in judgement about other contributors. We suggest design opportunities and challenges that apply these results to the design of medical crowdfunding interfaces.

Medical crowdfunding helps patients receive financial support from their distributed social networks online. However, little is known about who the patient's supporters are, what support they provide, and why. To address this, we interviewed fifteen people involved in medical crowdfunding, including both beneficiaries and supporters. We found that support networks were larger than beneficiaries expected, with strangers offering support. Supporters offered not only monetary but also volunteering contributions including campaign creation, promotion, and external support. However, the emphasis medical crowdfunding interfaces place on monetary contributions led to social issues. Beneficiaries' close friends felt pressured to donate money they could not afford to give. And beneficiaries promoting the campaign worried they would be judged for requesting money. To mitigate these concerns, we suggest making the variety of volunteering contributions more visible and discuss the design challenges of including such signals in existing systems.

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.

Building social support networks is crucial both for less-independent individuals with autism and for their primary caregivers. In this paper, we describe a four-week exploratory study of a social network service (SNS) that allows young adults with autism to garner support from their family and friends. We explore the unique benefits and challenges of using SNSs to mediate requests for help or advice. In particular, we examine the extent to which specialized features of an SNS can engage users in communicating with their network members to get advice in varied situations. Our findings indicate that technology-supported communication particularly strengthened the relationship between the individual and extended network members, mitigating concerns about over-reliance on primary caregivers. Our work identifies implications for the design of social networking services tailored to meet the needs of this special needs population.

Independence is key to a successful transition to adulthood for individuals with autism. Social support is a crucial factor for achieving adaptive self-help life skills. In this paper we describe the results of a formative design exercise with young adults with autism and their caregivers to uncover opportunities for social networks to promote independence and facilitate coordination. We propose the concept of SocialMirror, a device connected to an online social network that allows the young adult to seek advice from a trusted and responsive network of family, friends and professionals. Focus group discussions reveal the potential for SocialMirror to increase motivation to learn everyday life skills among young adults with autism and to foster collaboration among a distributed care network. We present design considerations to leverage a small trusted network that balances quick response with safeguards for privacy and security of young adults with autism.