GeniAuti: Toward Data-Driven Interventions to Challenging Behaviors of Autistic Children through Caregivers' Tracking
Eunkyung Jo, Seora Park, Hyeonseok Bang, Youngeun Hong, Yeni Kim, Jungwon Choi, Bung-Nyun Kim, Daniel A. Epstein, Hwajung Hong
Abstract
Challenging behaviors significantly impact learning and socialization of autistic children and can stress and burden their caregivers. Documentation of challenging behaviors is fundamental for identifying what environmental factors influence them, such as how others respond to a child's such behaviors. Caregiver-tracked data on their child's challenging behaviors can help clinical experts make informed recommendations about how to manage such behaviors. To support caregivers in recording their children's challenging behaviors, we developed GeniAuti, a mobile-based data-collection tool built upon a clinical data collection form to document challenging behaviors and other clinically relevant contextual information such as place, duration, intensity, and what triggers such behaviors. Through an open-ended deployment with 19 parent-child pairs and three expert collaborators, caregivers found GeniAuti valuable for (1) becoming more attentive and reflective to behavioral contexts, including their own response strategies, (2) discovering positive aspects of their children's behaviors, and (3) promoting collaboration with clinical experts around the caregiver-tracked data to develop tailored intervention strategies for their children. However, participant experiences surface challenges of logging behaviors in social circumstances, conflicting views between caregivers and clinical experts around the structured recording process, and emotional struggles resulting from recording and reflecting on intensely negative experiences. Considering the complex nature of caregiver-based health tracking and caregiver--clinician collaboration, we suggest design opportunities for facilitating negotiations between caregivers and clinicians and accounting for caregivers' emotional needs.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 31e07701-12c8-493d-be4d-582d731074daCited by top-tier papers10
- Understanding the Benefits and Challenges of Deploying Conversational AI Leveraging Large Language Models for Public Health InterventionEunkyung Jo, Daniel A. Epstein, Hyunhoon Jung, Young-Ho KimCHI 2023 · 167 citations
- Unpacking the Lived Experiences of Smartwatch Mediated Self and Co-Regulation with ADHD ChildrenLucas M. Silva, Franceli L. Cibrian, Elissa Monteiro, Arpita Bhattacharya et al.CHI 2023 · 56 citations
- Beyond the Bulging Binder: Family-Centered Design of a Digital Health Information Management System for Caregivers of Children Living with Health ComplexityKatayoun Sepehri, Liisa Holsti, Sara Niasati, Vita Chan et al.CHI 2023 · 27 citations
- Unpacking the Lived Experience of Collaborative Pregnancy TrackingXi Lu, Jacquelyn E. Powell, Elena Agapie, Yunan Chen et al.CHI 2024 · 21 citations
- Examining the Social Aspects of Pregnancy Tracking ApplicationsXi Lu, Jacquelyn E. Powell, Elena Agapie, Yunan Chen et al.CSCW 2024 · 14 citations
Builds on9
- Mapping and Taking Stock of the Personal Informatics LiteratureDaniel A. Epstein, Clara Marques Caldeira, Mayara Costa Figueiredo, Xi Lu et al.UbiComp 2021 · 223 citations
- DreamCatcher: Exploring How Parents and School-Age Children can Track and Review Sleep Information TogetherLaura R. Pina, Sang-Wha Sien, Clarissa Song, Teresa M. Ward et al.CSCW 2020 · 83 citations
- TalkingBoogie: Collaborative Mobile AAC System for Non-verbal Children with Developmental Disabilities and Their CaregiversDonghoon Shin, Jaeyoon Song, Seokwoo Song, Jisoo Park et al.CHI 2020 · 45 citations
- Divided We Stand: The Collaborative Work of Patients and Providers in an Enigmatic Chronic DiseaseAdrienne Pichon, Kayla Schiffer, Emma Horan, Bria Massey et al.CSCW 2020 · 43 citations
- MAMAS: Supporting Parent-Child Mealtime Interactions Using Automated Tracking and Speech RecognitionEunkyung Jo, Hyeonseok Bang, Myeonghan Ryu, Eun Jee Sung et al.CSCW 2020 · 35 citations
Related papers
- Collaborative Aspects of Collecting and Reflecting on Behavioral DataGabriela Marcu, Allison Nicole SpillerCHI 2020 · 13 citations
- CareAssist: Supporting Offline Caregiver Coaching in Daily Autism Care through Multimodal Sensing and LLMsJunxiao Chen, Chenchen Xu, Yujing Zhang, Ting Zhou et al.UbiComp 2026
- "Chasing Shadows": Understanding Personal Data Externalization and Self-Tracking for Neurodivergent IndividualsTanya Rudberg Selin, Danielle Unéus, Søren KnudsenCHI 2026 · 1 citation
- Situated Use and Negotiated Effectiveness: Critical Considerations of GenAI-Powered Reminiscence Intervention for People with DementiaYuling Sun, Zhennan Yi, Junyan Mao, Minglong Tang et al.CSCW 2026
- De-centering Inclusivity: Fitting Design for Aut-EthnographySarah Fjelsted Alrøe, Peter Gall KroghCHI 2025 · 2 citations
