FamilyBloom: Examining Ecologies of Collaboration in Family-Centered Health Tracking

Lucas M. Silva; Aehong Min; Evropi Stefanidi; Franceli L. Cibrian; Jesus A. Beltran; Cassie Zeiler; Sabrina Schuck; Kimberley D Lakes; Gillian R. Hayes; Daniel A. Epstein

doi:10.1145/3772318.3791277

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FamilyBloom: Examining Ecologies of Collaboration in Family-Centered Health Tracking

Conference proceeding

Open access

Peer reviewed

FamilyBloom: Examining Ecologies of Collaboration in Family-Centered Health Tracking

Lucas M. Silva, Aehong Min, Evropi Stefanidi, Franceli L. Cibrian, Jesus A. Beltran, Cassie Zeiler, Sabrina Schuck, Kimberley D Lakes, Gillian R. Hayes and Daniel A. Epstein

Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, pp.1-24

ACM Conferences

CHI 2026: CHI Conference on Human Factors in Computing Systems

04/13/2026

DOI: 10.1145/3772318.3791277

Appears in UI Libraries Support Open Access

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Abstract

Family health informatics tools can help support well-being with shared data tracking. Prior work typically focused on shared data review, but often in specific moments, like bedtime, or centered on caregiving of children or elderly members. To investigate how tracking can support mutual health collaboration between family members pervasively across daily contexts, we designed and deployed FamilyBloom, a glanceable smartwatch and home display system for mood and goal tracking. Twelve families with both neurotypical and ADHD members used FamilyBloom for three months on average. Our findings reveal how family-centered tracking created collaboration opportunities and tensions across multiple ecological systems: individual self-regulation, collaborations within family dynamics, involvement of care networks with varying trust levels, institutional school constraints and cultural stigma, and temporality of regular routines and crisis periods. We discuss an ecosystem-aware approach to family informatics, wherein design can attend to how families navigate multiple contexts while sustaining family-level collaboration.

Human-centered computing -- Empirical studies in collaborative and social computing

Human-centered computing -- Ubiquitous and mobile devices

Information systems -- Information systems applications

UIOWA OA Agreement

Details

Title: Subtitle: FamilyBloom: Examining Ecologies of Collaboration in Family-Centered Health Tracking
Creators: Lucas M. Silva - University of Iowa
Aehong Min - University of California, Irvine
Evropi Stefanidi - TU Wien
Franceli L. Cibrian - Chapman University
Jesus A. Beltran - California State University Los Angeles
Cassie Zeiler - University of California, Irvine
Sabrina Schuck - University of California, Irvine
Kimberley D Lakes - University of California, Riverside
Gillian R. Hayes - University of California, Irvine
Daniel A. Epstein - University of California, Irvine
Contributors: Nuria Oliver (Editor) - ELLIS Alicante
David A. Shamma (Editor) - MBZUAI
Heloisa Candello (Editor) - Inteli
Pablo Cesar (Editor) - CWI
Pedro Lopes (Editor) - University of Chicago
Alessandro Bozzon (Editor) - Delft University of Technology
Thomas Kosch (Editor) - Humboldt-Universität zu Berlin
Vera Liao (Editor) - University of Michigan
Xiaojuan Ma (Editor) - The Hong Kong University of Science and Technology (Guangzhou)
Valentino Artizzu (Editor) - University of Cagliari
Fiona Draxler (Editor) - University of Mannheim
Gustavo López (Editor) - Universidad de Costa Rica
Anke V. Reinschluessel (Editor) - University of Konstanz
Xin Tong (Editor) - The Hong Kong University of Science and Technology (Guangzhou)
Phoebe O. Toups Dugas (Editor) - Monash University
Resource Type: Conference proceeding
Publication Details: Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, pp.1-24
Conference: CHI 2026: CHI Conference on Human Factors in Computing Systems
Series: ACM Conferences
DOI: 10.1145/3772318.3791277
Publisher: Association for Computing Machinery (ACM)
Language: English
Date published: 04/13/2026
Academic Unit: Computer Science
Record Identifier: 9985152241202771

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