Neurodiversity perspectives have in recent years made headway in HCI, broadening the role of autistic people. Outside HCI, an essential tool of the neurodiversity movement is the use of first person methods such as autoethnography. This paper explores how interaction design may contribute to ease the burden of conducting Autistic autoethnography (aut-ethnography), and how aut-ethnography may contribute to HCI. Taking an autoethnographic approach in the design of a set of recording devices, we identify three design sensitivities when designing for aut-ethnography: Inertial, sensory, and social fit. We further nuance these in an exploratory trial with other autistic people. We conclude that designing for the context of aut-ethnography requires significant adaptability of the designed artifacts in order to facilitate maintenance of existing rhythms in practice and adhere to fine-grained idiosyncratic preferences and ideals of practicing care and fairness.
https://dl.acm.org/doi/10.1145/3706598.3713942
Previous work on Social Comparison Theory shows that comparing oneself to others can lead to negative self-perceptions and rumination, reducing self-confidence. Despite these harmful effects, social comparisons are frequently used as engagement strategies in personal informatics systems, such as health and wellness apps. There is limited understanding of how users perceive these comparisons and their impact on wellbeing. To address this, we reviewed the Top 50 Health & Wellness smartphone applications to analyse implemented comparison strategies and the metrics such comparisons are used for. We conducted an online vignette study (n=192) and an interview study (n=12) to further explore the impact of social comparisons on users. Our study shows that comparisons in personal informatics motivate users but simultaneously lead to negative emotions (e.g., inferiority, disappointment), potentially leading to obsessive thoughts and overtraining. Based on our findings, we propose design guidelines for implementing social comparison features that prioritise users’ wellbeing.
https://dl.acm.org/doi/10.1145/3706598.3713737
Research and technological advancements have driven the development of wearable technology for stress management. Previous reviews primarily focused on its performance and effectiveness in health contexts. In contrast, this review takes a human-centric approach and reviews studies on users’ attitudes and experiences. We conducted a narrative review to identify (1) the facilitators and barriers of wearable stress management technology (WSMT) and (2) design considerations for human-centered WSMT. We identified 28 articles reporting user perspectives on stress management technology, primarily based on evaluation studies in which user perspectives were gathered through qualitative methods. We found five facilitators and barriers of WSMT (i.e., usefulness, functionality/interactivity, seamlessness, user privacy, and technology’s image). Additionally, we synthesized 18 design considerations, highlighted two main design challenges, and proposed a value-sensitive approach for future research. This review adds to the HCI literature by demonstrating the complexity of designing human-centered WSMT and the need for actionable recommendations.
https://dl.acm.org/doi/10.1145/3706598.3713802
Auditory sense is the primary channel for people with blind and low vision (BLV) to access information. This paper aims to understand the productization of individual voices of BLV voice actors in the audiobook industry. We conducted online semi-interviews with the BLV voice actors in China (N = 13) and gained insights into the workflow through offline observations. Interviews indicate that the ability to match job requirements, social benefits, and accessible support are key factors that draw BLV people into this field. They acquire vocal techniques, actively showcase their voices, and adapt their career paths as needed. Social support is crucial for their continued employment, as well as disclosing their BLV identities as appropriate. Observations reveal that BLV people utilize text processing tools, Screen Reader(SR) speed control, and keyboard shortcuts to transform an invisible script into a coherent and emotionally nuanced voice recording. We investigate how BLV people harness their potential through intensive voice acting while listening to SR, and proficient keyboard skills for software access.
https://dl.acm.org/doi/10.1145/3706598.3713636
Transgender people often use face filters to try and see different possible futures: versions of what they might look like during or post transition, or how they might appear in an ideal future or alternate world. However, there are effectively no face filters made for trans people to feel good using. As a result, people often end up feeling bad or dysphoric instead of supported in their pursuit to envision the future. We asked 44 trans people about augmented reality and face filters, and to speculate on future technologies that would support their wellbeing and desires for transition. We found that trans-affirming face filters would be designed to support data privacy, agency, intersectionality, and consideration for expansive identity categories. Meeting these design goals would enable trans people to explore many different radically possible futures, facilitating expansive, transformative, self-perceptions that honor the multiplicity inherent in trans identity.
People frequently exposed to health information on social media tend to overestimate their symptoms during online self-diagnosis due to availability bias. This may lead to incorrect self-medication and place additional burdens on healthcare providers to correct patients' misconceptions. In this work, we conducted two mixed-method studies to identify design goals for mitigating availability bias in online self-diagnosis. We investigated factors that distort self-assessment of symptoms after exposure to social media. We found that availability bias is pronounced when social media content resonated with individuals, making them disregard their own evidences. To address this, we developed and evaluated three chatbot-based symptom checkers designed to foster evidence-based self-reflection for bias mitigation given their potential to encourage thoughtful responses. Results showed that chatbot-based symptom checkers with cognitive intervention strategies mitigated the impact of availability bias in online self-diagnosis.
https://dl.acm.org/doi/10.1145/3706598.3713805