Boundary Negotiating Artifacts in Personal Informatics

Chung, Chia-Fang; Dew, Kristin; Cole, Allison; Zia, Jasmine; Fogarty, James; Kientz, Julie A.; Munson, Sean A.

doi:10.1145/2818048.2819926

Cited by 193 publications

(116 citation statements)

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“…This research tends to focus on behaviour, social collaborative practices and the agency of patients and clinicians as opposed to an explicit focus on experience. For example, Grönvall and Verdezoto [17] explored the non-functional aspects in everyday selfmonitoring activities such as motivation and routines, Nunes and Fitzpatrick [26] show how self-care is a collaborative process involving family and relatives and Chung et al [9] study expectations in collaboration practices around patient-generated data. Some user studies do consider the emotional side of healthcare technologies.…”

Section: Hci and Cscw User Studies In Healthcarementioning

confidence: 99%

Understanding patient experience

Andersen

Kornum

et al. 2017

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare

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The term 'patient experience' is currently part of a global discourse on ways to improve healthcare. This study empirically explores what patient experience is in cardiac remote monitoring and considers the implications for user experience (UX). Through interviews around the deployment of a mobile app that enables patients to collaborate with clinicians, we unpack experiences in six themes and present narratives of patients' lifeworlds. We find that patients' emotions are grounded in negative feelings (uncertainty, anxiety, loss of hope) and that positive experiences (relief, reassurance, safety) arise from getting feedback on symptoms and from continuous and comforting interaction with clinicians. With this paper, we aim to sensitise UX researchers and designers of patientcentred e-health by proposing three UX dimensions: connectedness, comprehension, and compassion.

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Section: Hci and Cscw User Studies In Healthcarementioning

confidence: 99%

Understanding patient experience

Andersen

Kornum

et al. 2017

Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare

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show abstract

“…At the same time, clinicians can find patient-generated data overwhelming, unreliable, and clinically irrelevant [59]. Patients may collect data on different topics from what clinicians would prescribe [46], in part because the tools they use are not designed flexibly enough to support customized goals [8]. Patients and clinicians may have misaligned goals, leading to frustration on both sides [8].…”

Section: Related Workmentioning

confidence: 99%

Supporting Collaborative Health Tracking in the Hospital

Mishra

Miller

Haldar

et al. 2018

Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

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The hospital setting creates a high-stakes environment where patients’ lives depend on accurate tracking of health data. Despite recent work emphasizing the importance of patients’ engagement in their own health care, less is known about how patients track their health and care in the hospital. Through interviews and design probes, we investigated hospitalized patients’ tracking activity and analyzed our results using the stage-based personal informatics model. We used this model to understand how to support the tracking needs of hospitalized patients at each stage. In this paper, we discuss hospitalized patients’ needs for collaboratively tracking their health with their care team. We suggest future extensions of the stage-based model to accommodate collaborative tracking situations, such as hospitals, where data is collected, analyzed, and acted on by multiple people. Our findings uncover new directions for HCI research and highlight ways to support patients in tracking their care and improving patient safety.

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“…Although much research has focused on tracking for general health and wellness (e.g., [30][31][32]), people who live with a chronic illness have further tracking requirements central to illness management that provide a rich opportunity for understanding through research. Furthermore, research examining the lived experiences of self-tracking find that this act of tracking is often coordinated or influenced by communication with health experts (e.g., [24,28,33]), with peers (e.g., [34]), with friends and acquaintances (e.g., [35]), among family members (e.g., [36]), and with workplace colleagues and by workplace programs (e.g., [37]). …”

Section: Social Factors Of Self-managementmentioning

confidence: 99%

“…Q14 even used the quality of her handwriting in her headache journal as an additional indicator of headache severity. Chung et al [33] similarly discussed various types of collection, as well as boundary negotiating artifacts generated through tracking.…”

Section: Collectionmentioning

confidence: 99%

“It’s Not Just Technology, It’s People”: Constructing a Conceptual Model of Shared Health Informatics for Tracking in Chronic Illness Management (Preprint)

Vizer¹,

Eschler²,

Koo³

et al. 2018

Preprint

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Background: Chronic illness is a substantial public health burden and the day-to-day work of a person with chronic illness is central to illness management. However, although management programs are available to train people to manage their chronic illnesses, those programs rarely provide people with sufficient guidance on implementing fine-grained management strategies. This lack of guidance transfers much of the burden of day-to-day management practices to people with chronic illness. Objective: To decrease the management burden many people have created technological solutions, but we claim that to be maximally effective and tailored to people's needs, those solutions need to be informed by a model that integrate patient work and self-management frameworks with personal health informatics models. We see an opportunity to improve personal health informatics models to (1) incorporate the ongoing nature of management work, and (2) append a social dimension to more accurately depict the context of illness management. Methods:We used qualitative methods to analyze the chronic illness management practices of 63 people through the lenses of self-management and informatics frameworks. Results: Analysis results are distilled into a new Conceptual Model of Shared Health Informatics. We describe the people and work involved in chronic illness management and contribute a Conceptual Model of Shared Health Informatics depicting the process of chronic illness management in a social context. Conclusions: Through insight into management work provided by our Conceptual Model of Shared Health Informatics, technology designers and implementers can improve the quality of chronic illness management tools to ensure confident and capable management of chronic illness.

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Boundary Negotiating Artifacts in Personal Informatics

Cited by 193 publications

References 50 publications

Understanding patient experience

Understanding patient experience

Supporting Collaborative Health Tracking in the Hospital

“It’s Not Just Technology, It’s People”: Constructing a Conceptual Model of Shared Health Informatics for Tracking in Chronic Illness Management (Preprint)

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